quora_siamese_lstm: Classifying duplicate quesitons from Quora using Siamese Recurrent Architecture. 5 million pairs. How to predict Quora Question Pairs using Siamese Manhattan LSTM Mar 13, 2016. It includes 404351 question pairs with a label column indicating if they are duplicate or not. The final model implemented is Siamese LSTM to classify pairs of sentences as either the same question or different. We propose to solve the semantic question matching problem for duplicate question pair detection, using a hybrid deep learning model, which combines a Co-attention based Bi-Directional Long Short-Term Memory (Bi-LSTM) Siamese neural network and a Multi-layer perceptron classifier to output the probability of a similarity match between the two. We trained our own word embeddings using Quora's text corpus, combined them to generate question embeddings for the two questions, and then fed those question embeddings into a representation layer. in a collection of n= 10000 sentences the pair with the highest similarity requires with BERT n(n 1)=2 = 49995000inference computations. Provide details and share your research! But avoid … Asking for help, clarification, or responding to other answers. The model achieved an accuracy of 80% on test data. Wherever the binary value is 1, the question in the pair are not identical; they are rather paraphrases of each-other. Siamese LSTM for evaluating semantic similarity between sentences of the Quora Question Pairs Dataset. The dataset consists of over 400,000 pairs of questions and corresponding labels indicating whether the two questions in a pair have the same intent. fit, I test the model using model. The question then is: how well can we teach a computer program to demonstrate the ability to understand meaning? We examine this overarching question within the context of the Quora Questions dataset. Classifying semantic equivalence of quora question pairs using Deep Learning based LSTM Feb 2018 - Present We used Quora's 400,000 question pairs as the dataset. CNN, and BERT + Linear. I will do my best to explain the network and go through the Keras code (if you are only here for the code, scroll down :) Full code on Github In. The rest of the paper is organized as follows: Section II describes the architecture. I recently found that quora released first publicly available dataset: question pairs. The model architecture is based on the Stanford Natural Language Inference [2] benchmark model developed by Stephen Merity [3], specifically the version using a simple summation of GloVe word embeddings [4] to represent each question in the pair. TensorFlow for R. Introduction. Quora Question Pairs Jan 2019 - Feb 2019 • The main objective of the project is to find the similarity of two questions posted on Quora. The performance of Quora is measured by accuracy. View Aman Singh Verma's profile on LinkedIn, the world's largest professional community. The dataset first appeared in the Kaggle competition Quora Question Pairs and consists of approximately 400,000 pairs of questions along with a column indicating if the question pair is considered a duplicate. text #Prepare embedding of the data — I am using quora question pairs for dataset in. fit, I test the model using model. Question 1, question 2: The actual textual contents of the questions. Finally, estimates of precision and recall from the deployment of our automated assistant suggest that we can expect the burden on our HR department to drop from answering about 6000 queries a. Figure 2: Siamese LSTM Network is the label for ordered translation pair t ij and t ik, where j 6= k. These are split into test and training dataset. TensorFlow for R. I just want to. 유사한 질문을 찾아내는 알고리즘을 고민하고 있던 중 Kaggle에서 Quora의 유사 질문을 찾는 Quora Question Pairs Competition을 알게 되었고, 여기에서 평가가 매우 좋은 Siamese LSTM 네트워크를 이용한 문장의 의미론적 유사도를 판별하는 논문을 살펴보고 구현을 진행해보았습니다. ,2015), SICK (Marelli et al. Implementing MaLSTM on Kaggle's Quora Question Pairs competition. We had counts of neighbors of question 1, question 2, the min, the max, intersections, unions, shortest path length when main edge cut…. Exper- The models are developed from Siamese architecture [2] and aim to find a fixed-length vector representation for each of the performance of LSTM. reuters_mlp: Trains and evaluatea a simple MLP on the Reuters newswire topic classification task. Quora recently released the first dataset from their platform: a set of 400,000 question pairs, with annotations indicating whether the questions request the same information. LSTM for Question 1 how to make friends ? T 5 T 6 T 7 T 8 9 D 5 6 7 D 8 LSTM for Question 2 X %' :U ÜáU ; Element-wise multiplication Figure3: Architecture1:The first naive approach considered two LSTM RNNs to parse the pair of questions. Data fields. Deep Contextualized Pairwise Semantic Similarity for Arabic Language Questions. On the second paper, they don't mention which classifier they use to classify samples from the embedding learned vectors (they only talk about euclidian distance whitin. Quora Question Pair dataset is collected from the real-world questions on Quora website. class: center, middle, inverse, title-slide # Keras: Deep Learning com R ## rday-keras. In these blog posts series, I’ll describe my experience getting hands-on experience participating in it. 002 gain in private and public leaderboard respectively. 1 Dataset We evaluated our models on the Quora question paraphrase dataset which contains over 404,000 question pairs with binary labels. Implementation details. We reduce the computational complexity by. CNN, and BERT + Linear. Good luck!. [14] introduced a Con-. atively few pairs of questions (few thou-sands) as gold standard (GS) training data is typically scarce, (ii) predicting labels on a very large corpus of question pairs, and (iii) pre-training NNs on such large cor-pus. The article is about Manhattan LSTM (MaLSTM) — a Siamese deep network and its appliance to Kaggle’s Quora Pairs competition. Those rows do not come from Quora, and are not counted in the scoring. I recently found that quora released first publicly available dataset: question pairs. In this iteration I first attempt to use word2vec embeddings, then bert embedings, and finally training embeddings with the model. The problem of question pairs matching aims to seek whether the underlying semantics of two questions are equivalent. The architecture of the LSTM + GRU model is as follows: 1. Previous approaches either match sentences from a single direction or only apply single granular (word-by-word or sentence-by-sentence) matching. predict on the test data. reuters_mlp: Trains and evaluatea a simple MLP on the Reuters newswire topic classification task. Moreover, they also started Kaggle competition based on that dataset. Exper- The models are developed from Siamese architecture [2] and aim to find a fixed-length vector representation for each of the performance of LSTM. In this competition, Kagglers are challenged to tackle this natural language processing problem by applying advanced techniques to classify whether question pairs are duplicates or not. 84586, achieving fourth place in the final test. 1) I have set trainable=False because I am using a pre-trained word embeddings. Read writing about Recurrent Neural Network in ML Review. The test labels are 0 or 1. [Mueller and Thyagarajan, 2016] used Siamese LSTMs for NLI. Currently, Quora uses a Random Forest model to identify duplicate questions. Training dataset used is a subset of the original Quora Question Pairs Dataset(~363K pairs used). I will do my best to explain the network and go through the Keras code (if you are only here for the code, scroll down :) Full…. We present experimental results from our deployment showing that our iteratively trained hybrid network: (a) results in. Previous researches regard such problem as question matching task: given a pair of questions, the supervised models learn question representation and predict it similar or not. , 2014), etc. The dataset first appeared in the Kaggle competition Quora Question Pairs. Making statements based on opinion; back them up with references or personal experience. It is Keras implementation based on Original Paper(PDF) and Excellent Medium Article. LSTM for Question 1 how to make friends ? T 5 T 6 T 7 T 8 9 D 5 6 7 D 8 LSTM for Question 2 X %' :U ÜáU ; Element-wise multiplication Figure3: Architecture1:The first naive approach considered two LSTM RNNs to parse the pair of questions. Detecting Duplicate Quora Questions. $ python3 keras-quora-question-pairs. 1 LSTM + GRU (Baseline) We reimplement a LSTM + GRU model has been shown to perform well for this task [1]. These datasets provide resources for both training and evaluation of different algo-rithms (Torralba and Efros,2011). fit, I test the model using model. I have updated the question with brief dataset description and the goal of the model. 5 million pairs. The private leaderboard is calculated with approximately 94% of the test data. September 25, 2017. classi ed question-question pairs. The test labels are 0 or 1. - Trained an Siamese-LSTM with a binary cross entropy loss using Quora Question Pairs training set. The model architecture is based on the Stanford Natural Language Inference [2] benchmark model developed by Stephen Merity [3], specifically the version using a simple summation of GloVe word embeddings [4] to represent each question in the pair. Quora Questions’ Pair Dataset Quora Questions’ Pair Dataset contains question pairs from the Q&A website2 tagged as similar or not. The brothers were from Siam, hence the name Trains a Siamese MLP on pairs of digits from the MNIST. The dataset first appeared in the Kaggle competition Quora Question Pairs and consists of approximately 400,000 pairs of questions along with a column indicating if the question pair is considered a duplicate. A random 90%-10% train-test split is performed as is customary for other methods and the model is trained on the train set and evaluated on the test set. FIGURE 1 - Siamese CNN+LSTM to calculate the similarity of a pair of sentences. predict on the test data. The dataset first appeared in the Kaggle competition Quora Question Pairs and consists of approximately 400,000 pairs of questions along with a column indicating if the question pair is considered a duplicate. Duplicate Question Identification by Integrating FrameNet with Neural Networks Xiaodong Zhang,1 Xu Sun,1 Houfeng Wang1,2 1 MOE Key Lab of Computational Linguistics, Peking University, Beijing, 100871, China 2 Collaborative Innovation Center for Language Ability, Xuzhou, Jiangsu, 221009, China {zxdcs, xusun, wanghf}@pku. Quora Question Pairs Can you identify question pairs that have the same intent? $25,000 Prize Money. The results on Quora and SemEval question similarity datasets show that NNs trained with our approach can learn more. com containing over 400K annotated question pairs containing binary paraphrase labels. - Received a log loss of 0. #Prepare embedding of the data - I am using quora question pairs: for dataset in [train_df, test_df]: for index, row in dataset. The rest of the paper is organized as follows: Section II describes the architecture. The dataset first appeared in the Kaggle competition Quora Question Pairs. ∙ Mawdoo3 ∙ 0 ∙ share. The output is an array of values something like below:. The term 'Siamese twins' derives from Chang and Eng Bunker (1811-1874) who were the first pair of conjoined twins to become internationally known. Kaggle Quora Question Pairs [Keras, scikit-learn, Matplotlib] Dec 2017 – Dec 2017 Trained Siamese LSTM based Neural Network to predict whether a given pair of question pairs have the same intent or not. Attempted pretrained bert embeddings, Word2Vec and training own embeddings together with the model. Quora Question Pair Similarity using Siamese LSTM's Dec 2018 - Apr 2019. Quora Questions’ Pair Dataset Quora Questions’ Pair Dataset contains question pairs from the Q&A website2 tagged as similar or not. !LSTM Figure 3 shows my LSTM model. We present experimental results from our deployment showing that our iteratively trained hybrid network: (a) results in. Using a data set question pairs provided by Quora in Kaggle, we extract the features from the data set by using some methods like common word share, Jaccard Similarity Coefcient, Cosine Similarity, Tf-Idf. Finally, two scores are summed and followed by a logistic layer, to predict the label p. fit, I test the model using model. 35% on Quora Question Pairs Dataset; Semantic similarity between current sentence and sentences in the corpus was used for. 55 BiMPM 88. ,2015), SICK (Marelli et al. [Mueller and Thyagarajan, 2016] used Siamese LSTMs for NLI. We propose a novel approach of Siamese LSTM Net-work, which learns long term dependencies and capture sequential patterns present in the question and its related question, which was missing in the T-SCQA [15]. The non-duplicate. September 10, 2017 — 0 Comments. Classifying semantic equivalence of quora question pairs using Deep Learning based LSTM Feb 2018 - Present We used Quora's 400,000 question pairs as the dataset. 522 12 LSTM All Avg SVOR LSTM-AvgPool-SVOR 0. Making statements based on opinion; back them up with references or personal experience. Recently, there emerge many methods, such as ABCNN [23], Siamese LSTM [19] and L. The solution uses a support vec-. The dataset first appeared in the Kaggle competition Quora Question Pairs and consists of approximately 400,000 pairs of questions along with a column indicating if the question pair is considered a duplicate. Quora Question Pairs Dataset which is publically available on Kaggle has been used to train the Siamese LSTM Model. 1 indicates the question pair is duplicate. In addition, there does not exist a finely annotated question pairs dataset in Chinese medical domain. Implementing MaLSTM on Kaggle's Quora Question Pairs competition. It's free, confidential, includes a free flight and hotel, along with help to study to pass interviews and negotiate a high salary!. I would like to train multiple models on the same data using Keras, as an exercise for me to get acquainted with hyperparameter tuning in Keras for R (in Python, I use a different approach based on the Python library hyp…. In this competition, Kagglers are challenged to tackle this natural language processing problem by applying advanced techniques to classify whether question pairs are duplicates or not. The dataset first appeared in the Kaggle competition Quora Question Pairs and consists of approximately 400,000 pairs of questions along with a column indicating if the question pair is considered a duplicate. Moreover, identifying questions with the same semantic content could help web-scale question answering systems that are increasingly concentrating on retrieving focused answers to users’ queries. [14] introduced a Con-. - Ensembled LSTM predictions with XGBoost predictions. Home Installation Tutorials Guide Deploy Tools API Learn Blog. Deep Contextualized Pairwise Semantic Similarity for Arabic Language Questions. Wherever the binary value is 1, the question in the pair are not identical; they are rather paraphrases of each-other. Siamese-CNN 79. The second question was then fed into the second LSTM and let h N be the final output vector of the second LSTM. !LSTM Figure 3 shows my LSTM model. I have built a LSTM model to predict duplicate questions on the Quora official dataset. In this iteration I first attempt to use word2vec embeddings, then bert embedings, and finally training embeddings with the model. 1109/APSIPA. Experimental results show that our models can make full use of the semantic information of the text, and the F1 value in the dataset pro-vided by the CCKS2018 question-intention matching task is 0. stateful_lstm: Demonstrates how to use stateful RNNs to model long sequences efficiently. Quora Question Pair Similarity using Siamese LSTM's Dec 2018 - Apr 2019. We also implement an LSTM + GRU model as a baseline, which is a known well-performing model on this task. The results on Quora and SemEval question similarity datasets show that NNs trained with our approach can learn more. 16 which placed us 3rd in class. The implementation of this architecture as well as other neural architec- The first naive approach considered two LSTM RNNs to parse the pair. In this project, the dataset consisted of different pairs of questions that were asked on the Quora Platform together with a class label that indicates whether the given pair are similar to each other. Siamese neural network based on the long short-term memory (LSTM) [3] to model the sentences and measure the similarity between two sentences. In this iteration I first attempt to use word2vec embeddings, then bert embedings, and finally training embeddings with the model. September 25, 2017. The first question was fed into the first LSTM, and its final hidden state was used as the first hidden state in the second LSTM. ,2015), SICK (Marelli et al. Quora Question Pairs Jan 2019 - Feb 2019 • The main objective of the project is to find the similarity of two questions posted on Quora. We use the data split provided in Wang et al. We present experimental results from our deployment showing that our iteratively trained hybrid network: (a) results in. chine translation [10] and removing redundancy questions in Quora website [19]. I just want to. The Quora dataset is developed for paraphrase identification (to detect duplicate questions). These, along with correct pairs, are used to train the Siamese network to drive apart the (hidden) representations of the misclassi ed pairs. Since Quora gives importance to similar questions problem, it want to provide a good experience for both the question seeker and writer. His simple model composed of one layer of convolution achieved excellent results on. Quora (www. Now, i want to create a LSTM model like the above examples and use it but i am getting the following error: Using TensorFlow backend. Quora Which is a Question Answering company has this problem in the context of duplicate questions. Implementation details. After building the model using model. The model achieved an accuracy of 80% on test data. Recently, there emerge many methods, such as ABCNN [23], Siamese LSTM [19] and L. To make use of this specific dataset, we fed pairs of questions through the multi-layer LSTM network and then through a fully connected layer to output a ‘0’ or a ‘1,’ depending on. ,2018), including QuoraQP1, SNLI (Bowman et al. I would like to train multiple models on the same data using Keras, as an exercise for me to get acquainted with hyperparameter tuning in Keras for R (in Python, I use a different approach based on the Python library hyp…. 9% in train, 17. To address the issue they developed their own algorithms to detect duplicate question. I recently started to play with the dataset from the Quora Question Pairs Challenge. The solution uses a support vec-. The brothers were from Siam, hence the name Trains a Siamese MLP on pairs of digits from the MNIST. On the second paper, they don't mention which classifier they use to classify samples from the embedding learned vectors (they only talk about euclidian distance whitin. dfalbel / quora-question-pairs. Quora Insincere Questions classification was the second kaggle competition hosted by quora with the objective to develop more scalable methods to detect toxic and misleading content on their platform. The test labels are 0 or 1. The final hidden states of each LSTM are combined by an element-wise multiplication. Quora Question Pairs Jan 2019 - Feb 2019 • The main objective of the project is to find the similarity of two questions posted on Quora. 09/19/2019 ∙ by Hesham Al-Bataineh, et al. The results on Quora and SemEval question similarity datasets show that NNs trained with our approach can learn more. After building the model using model. There were around 400K question pairs in the training set while the testing set contained around 2. They propose a generic framework for For instance,Mueller and Thyagara-jan(2016) propose a siamese recurrent architec-ture using Manhattan LSTM (MaLSTM) for STS. Each sample has two questions along with ground truth about their similarity(0 - dissimilar, 1- similar). CNN, and BERT + Linear. Take Quora Question Pairs dataset [15] as an instance: input data question 1 and question Siamese-CNN 79. 00238 and 0. Collectible Companions of Classic. They use word embeddings supplemented with synonymy information, LSTM and Manhattan dis-. Read writing about Keras in ML Review. The rest of the paper is organized as follows: Section II describes the architecture. Using Siamese LSTM to classify repeated quora questions. This is important for companies like Quora, or Stack Overflow where multiple questions posted are duplicates of questions already answered. Investigating Siamese LSTM networks for text categorization @article{Shih2017InvestigatingSL, title={Investigating Siamese LSTM networks for text categorization}, author={Chin-Hong Shih and Bi-Cheng Yan and Shih-Hung Liu and Berlin Chen}, journal={2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. cnAbstract There are two major problems in duplicate question identifi-. Implemented a Siamese LSTM model to identify similar questions from Quora based on their semantic similarity. We present a siamese adaptation of the Long Short-Term Memory (LSTM) network for labeled data comprised of pairs of variable-length sequences. fit, I test the model using model. F IGURE 1 – Siamese CNN+LSTM to calculate the similarity of a pair of sentences. I will do my best to explain the network and go through the Keras code (if you are only here for the code, scroll down :) Full…. I just want to. In this iteration I first attempt to use word2vec embeddings, then bert embedings, and finally training embeddings with the model. The rest of the paper is organized as follows: Section II describes the architecture. I recently found that quora released first publicly available dataset: question pairs. We had counts of neighbors of question 1, question 2, the min, the max, intersections, unions, shortest path length when main edge cut…. Siamese-CNN 79. CS224N Project: Natural Language Inference for Quora Dataset Kuy Hun Koh Yoo Energy Resources Engineering ory (LSTM) cells were applied to identify duplicate question-pairs in the Quora dataset. A binary value is assigned to each question pair indicating whether the two questions are the same or not. The dataset first appeared in the Kaggle competition Quora Question Pairs and consists of approximately 400,000 pairs of questions along with a column indicating if the question pair is considered a duplicate. [Severyn and Moschitti, 2015] used Siamese convnets to match candidate answer passages to queries. Figure 2: Siamese LSTM Network is the label for ordered translation pair t ij and t ik, where j 6= k. I recently started to play with the dataset from the Quora Question Pairs Challenge. Quora Question Pair Similarity using Siamese LSTM's Dec 2018 - Apr 2019. paraphrase-id-tensorflow - Various models and code (Manhattan LSTM, Siamese LSTM + Matching Layer, BiMPM) for the paraphrase identification task, specifically with the Quora Question Pairs dataset. cn Abstract. 5 million! A large majority of those pairs were computer-generated questions to prevent cheating, but 2 and a half million, god!. So, for our study, we choose all such question pairs with binary value 1. Good luck!. In this post, I'll explain how to solve text-pair tasks with deep learning, using both new and established tips and technologies. September 25, 2017. - Ensembled LSTM predictions with XGBoost predictions. 550 14 LSTM All EMD Logits LSTM-EMD-Logits 0. Natural language sentence matching is a fundamental technology for a variety of tasks. 1 Dataset We evaluated our models on the Quora question paraphrase dataset which contains over 404,000 question pairs with binary labels. CS224N Project: Natural Language Inference for Quora Dataset Kuy Hun Koh Yoo Energy Resources Engineering ory (LSTM) cells were applied to identify duplicate question-pairs in the Quora dataset. Data Overview. Attempted pretrained bert embeddings, Word2Vec and training own embeddings together with the model. The Manhattan LSTM [1] is simply a model using two LSTMs to measure similarity between a pair of sequences (query and document for eg. Thanks for contributing an answer to Web Applications Stack Exchange! Please be sure to answer the question. Finally, two scores are summed and followed by a logistic layer, to predict the label p. This competition has completed. It falls under the category of the Binary Classification Problem. Moreover, identifying questions with the same semantic content could help web-scale question answering systems that are increasingly concentrating on retrieving focused answers to users’ queries. More specifically, we used the Long Short Term Memory network (LSTM) variant of RNNs, which are better at capturing long-term dependencies. Quora Question Pair Similarity is a classic Sentiment Analysis problem used to classify whether the two given questions are same or not based upon the semantic meaning of the sentences. In addition, there does not exist a finely annotated question pairs dataset in Chinese medical domain. Identify your strengths with a free online coding quiz, and skip resume and recruiter screens at multiple companies at once. A random 90%-10% train-test split is performed as is customary for other methods and the model is trained on the train set and evaluated on the test set. There were around 400K question pairs in the training set while the testing set contained around 2. For this purpose, the authors present a subset of Quora data that consists of over 400,000 question pairs. py On first execution, this will download the required Quora and GloVe datasets and generate files that cache the training data and related word count and embedding data for subsequent runs. 522 12 LSTM All Avg SVOR LSTM-AvgPool-SVOR 0. Quora Question Pairs Can you identify question pairs that have the same intent? $25,000 Prize Money. edu Sukolsak Sakshuwong [email protected] When people come to the website, instead of finding a similar question that has been asked before, people post a new question, this leads to a lot o dup licate question. The dataset first appeared in the Kaggle competition Quora Question Pairs and consists of approximately 400,000 pairs of questions along with a column indicating if the question pair is considered a duplicate. Used Manhattan LSTM to predict semantic similarity of two query phrases; Google word2vec was used to generate embeddings of query phrases; Achieved an accuracy of 80. I have updated the question with brief dataset description and the goal of the model. !LSTM Figure 3 shows my LSTM model. The Manhattan LSTM [1] is simply a model using two LSTMs to measure similarity between a pair of sequences (query and document for eg. Previous approaches either match sentences from a single direction or only apply single granular (word-by-word or sentence-by-sentence) matching. id - the id of a training set question pair; qid1, qid2 - unique ids. Simply run the notebook server using the standard Jupyter command: $ jupyter notebook First run. ) The two LSTMs convert the variable length sequence into a fixed dimensional vector embedding. Duplicate Questions Pair Detection Using Siamese MaLSTM Abstract: Quora is a growing platform comprising a user generated collection of questions and answers. Conventionally, neural methodology aligns the sentence pair and then generates a matching score for paraphrase identification, [18, 19]. 8282104 Corpus ID: 3318226. We also implement an LSTM + GRU model as a baseline, which is a known well-performing model on this task. ,2015), SICK (Marelli et al. This competition has completed. As Jupyter notebooks. The dataset consists of over 400,000 pairs of questions and corresponding labels indicating whether the two questions in a pair have the same intent. An Ensemble Model Based on Siamese Neural Networks for the Question Pairs Matching Task Shiyao Xu, Shijia E, and Yang Xiang Tongji University, Shanghai 201804, P. edu Sukolsak Sakshuwong [email protected] The problem we are trying to solve is: Given an ordered pair of. Data fields. class: center, middle, inverse, title-slide # Keras: Deep Learning com R ## rday-keras. I have used quora-questions pairs dataset and generated their embeddings using google-bert. 002 gain in private and public leaderboard respectively. text_explanation_lime: How to use lime to explain text data. Provide details and share your research! But avoid … Asking for help, clarification, or responding to other answers. from both directions of question pairs. 55 BiMPM 88. Quora recently released the first dataset from their platform: a set of 400,000 question pairs, with annotations indicating whether the questions request the same information. - Given a Questions pair, features are extracted from each question. A random 90%-10% train-test split is performed as is customary for other methods and the model is trained on the train set and evaluated on the test set. Browse The Most Popular 213 Lstm Open Source Projects. python keras Siamese LSTM Manhattan LSTM MaLSTM Semantic. Finally, two scores are summed and followed by a logistic layer, to predict the label p. How to predict Quora Question Pairs using Siamese Manhattan LSTM Mar 13, 2016. [13] combined a stack of character-level bidirectional LSTM with Siamese architec-ture to compare the relevance of two words or phrases. class: center, middle, inverse, title-slide # Keras: Deep Learning com R ## rday-keras. We also observe that using question-question pairs in our hybrid network, results in marginally better performance than using question-to-answer pairs. - Trained an Siamese-LSTM with a binary cross entropy loss using Quora Question Pairs training set. Each sample has two questions along with ground truth about their similarity(0 - dissimilar, 1- similar). The implementation of this architecture as well as other neural architec- The first naive approach considered two LSTM RNNs to parse the pair. Quora Question Pairs Can you identify question pairs that have the same intent? $25,000 Prize Money. We built density features from the graph built from the edges between pairs of questions inside train and test datasets concatenated. 유사한 질문을 찾아내는 알고리즘을 고민하고 있던 중 Kaggle에서 Quora의 유사 질문을 찾는 Quora Question Pairs Competition을 알게 되었고, 여기에서 평가가 매우 좋은 Siamese LSTM 네트워크를 이용한 문장의 의미론적 유사도를 판별하는 논문을 살펴보고 구현을 진행해보았습니다. When people come to the website, instead of finding a similar question that has been asked before, people post a new question, this leads to a lot o dup licate question. frequency of one question occurrence, the more probable that the question pair is duplicate, no matter what question is paired with it. The dataset first appeared in the Kaggle competition Quora Question Pairs. Implemented a Siamese LSTM model to identify similar questions from Quora based on their semantic similarity. We propose a novel approach of Siamese LSTM Net-work, which learns long term dependencies and capture sequential patterns present in the question and its related question, which was missing in the T-SCQA [15]. I have used quora-questions pairs dataset and generated their embeddings using google-bert. 11 LSTM All Max SVOR LSTM-MaxPool-SVOR 0. Quora Insincere Questions classification was the second kaggle competition hosted by quora with the objective to develop more scalable methods to detect toxic and misleading content on their platform. 60 Siamese-LSTM 82. 522 12 LSTM All Avg SVOR LSTM-AvgPool-SVOR 0. Quora recently announced the first public dataset that they ever released. The problem of question pairs matching aims to seek whether the underlying semantics of two questions are equivalent. The data will be downloaded internally in colab, you have to change few paths, only as this was connected to my google drive. Siamese neural network based on the long short-term memory (LSTM) [3] to model the sentences and measure the similarity between two sentences. edu Abstract We explored two approaches based on Long Short-Term Memory (LSTM) networks on the Quora duplicate question dataset. id - the id of a training set question pair; qid1, qid2 - unique ids. classi ed question-question pairs. After you complete this project, you can read about Quora’s approach to this problem in this blog post. In this tutorial we will use Keras to classify duplicated questions from Quora. In this iteration I first attempt to use word2vec embeddings, then bert embedings, and finally training embeddings with the model. Quora question-pair dataset expanded with paired answers. !Model choosing I implement two models in total, I will explain them below. Quora Question Pair dataset is collected from the real-world questions on Quora website. Exper- The models are developed from Siamese architecture [2] and aim to find a fixed-length vector representation for each of the performance of LSTM. On the second paper, they don't mention which classifier they use to classify samples from the embedding learned vectors (they only talk about euclidian distance whitin. classi ed question-question pairs. 5 million pairs. com) is a community-driven question and answer website where users, either anonymously or publicly, ask and answer questions. The Manhattan LSTM [1] is simply a model using two LSTMs to measure similarity between a pair of sequences (query and document for eg. Implemented a Siamese LSTM model to identify similar questions from Quora based on their semantic similarity. Deep Contextualized Pairwise Semantic Similarity for Arabic Language Questions. On January 30th, 2017, Quora released a dataset of over 400 thousand question pairs, some of were asking the same underlying question and other pairs which were not. Quora Question Duplication Elkhan Dadashov [email protected] QQP The Quora Question Pairs (QQP) dataset is a collection of question pairs from the community question-answering website Quora (Wang et al. This dataset consists of both "short" questions siamese LSTM(2) biLSTM+LSTM auc train 0. Manhattan LSTM model for text similarity. The article is about Manhattan LSTM (MaLSTM) — a Siamese deep network and its appliance to Kaggle’s Quora Pairs competition. A question in a pair with more than 1 sentence which would make We used the quora dataset[15] for duplicate questions. I have built a LSTM model to predict duplicate questions on the Quora official dataset. Bidirectional LSTM with attention on input sequence. 80 scoring. There are a total of 155 K such questions. The dataset consists of ~400k pairs of questions and a column indicating if the question pair is duplicated. The test labels are 0 or 1. Take Quora Question Pairs dataset [15] as an instance: input data question 1 and question 2 will be encoded as sentence representation !, " by the sentence encoder. The model architecture is based on the Stanford Natural Language Inference [2] benchmark model developed by Stephen Merity [3], specifically the version using a simple summation of GloVe word embeddings [4] to represent each question in the pair. Similar, finding which of the over 40 mil-lion existent questions of Quora is the most similar for a new question could be modeled as a pair-wise. The rest of the paper is organized as follows: Section II describes the architecture. The task is to determine whether a pair of. Because of this they hosted a competition called "Quora Question Pairs. I recently started to play with the dataset from the Quora Question Pairs Challenge. Duplicate Question Identification by Integrating FrameNet with Neural Networks Xiaodong Zhang,1 Xu Sun,1 Houfeng Wang1,2 1 MOE Key Lab of Computational Linguistics, Peking University, Beijing, 100871, China 2 Collaborative Innovation Center for Language Ability, Xuzhou, Jiangsu, 221009, China {zxdcs, xusun, wanghf}@pku. Read writing about Recurrent Neural Network in ML Review. Classifying semantic equivalence of quora question pairs using Deep Learning based LSTM Feb 2018 - Present We used Quora's 400,000 question pairs as the dataset. edu Abstract We explored two approaches based on Long Short-Term Memory (LSTM) networks on the Quora duplicate question dataset. The second question was then fed into the second LSTM and let h N be the final output vector of the second LSTM. The results on Quora and SemEval question similarity datasets show that NNs trained with our approach can learn more. The names MaLSTM and SiameseLSTM might leave an impression that there are some kind of new LSTM units proposed, but that is not the case. Home Installation Tutorials Guide Deploy Tools API Learn Blog. Highlights from Machine Learning Research, Projects and Learning Materials. CNN, and BERT + Linear. Implemented a Siamese LSTM model to identify similar questions from Quora based on their semantic similarity. Using a data set question pairs provided by Quora in Kaggle, we extract the features from the data set by using some methods like common word share, Jaccard Similarity Coefcient, Cosine Similarity, Tf-Idf. Quora Question Pairs Challenge Dataset So i did some basic stuff like visualizing the data a bit,cleaning it. id - the id of a training set question pair; qid1, qid2 - unique ids. Using Siamese LSTM to classify repeated quora questions. I have built a LSTM model to predict duplicate questions on the Quora official dataset. Siamese-CNN 79. This competition has completed. In SCQA, we overcome the non-availability of training data in the form of question-question pairs by leveraging existing question-answer pairs from the cQA archives which also helps in improving the effective-ness of the model. In this project, we focus on a dataset published by Quora. Quora recently released the first dataset from their platform: a set of 400,000 question pairs, with annotations indicating whether the questions request the same information. Quora Question Duplication Elkhan Dadashov [email protected] Duplicate Question Identification by Integrating FrameNet with Neural Networks Xiaodong Zhang,1 Xu Sun,1 Houfeng Wang1,2 1 MOE Key Lab of Computational Linguistics, Peking University, Beijing, 100871, China 2 Collaborative Innovation Center for Language Ability, Xuzhou, Jiangsu, 221009, China {zxdcs, xusun, wanghf}@pku. The Manhattan LSTM [1] is simply a model using two LSTMs to measure similarity between a pair of sequences (query and document for eg. Good luck!. The private leaderboard is calculated with approximately 94% of the test data. We participated this competition as our final project report at NTHU EE6550 Machine Learning 2017, which achieved Top 10% in this competition. It has 400,000 samples of potential question duplicate pairs. 80 scoring. 9% in train, 17. A binary value is assigned to each question pair indicating whether the two questions are the same or not. In our experiments, we evaluate our model on 50K, 100K and 150K training dataset sizes. Star 0 seq_emb <-layer_lstm. Quora Question Pairs Jan 2019 - Feb 2019 • The main objective of the project is to find the similarity of two questions posted on Quora. The data provided for training is from the public dataset from quora. Identifying Quora question pairs having the same intent Shashi Shankar [email protected] were input to a multi-layer LSTM-RNN architecture that out-puts one of the above classes. #Prepare embedding of the data - I am using quora question pairs: for dataset in [train_df, test_df]: for index, row in dataset. In these blog posts series, I’ll describe my experience getting hands-on experience participating in it. ,2018), including QuoraQP1, SNLI (Bowman et al. GitHub Gist: instantly share code, notes, and snippets. After you complete this project, you can read about Quora's approach to this problem in this blog post. They use word embeddings supplemented with synonymy information, LSTM and Manhattan dis-. The dataset first appeared in the Kaggle competition Quora Question Pairs. The first model uses a Siamese architecture with the learned representa-. 유사한 질문을 찾아내는 알고리즘을 고민하고 있던 중 Kaggle에서 Quora의 유사 질문을 찾는 Quora Question Pairs Competition을 알게 되었고, 여기에서 평가가 매우 좋은 Siamese LSTM 네트워크를 이용한 문장의 의미론적 유사도를 판별하는 논문을 살펴보고 구현을 진행해보았습니다. Let Y = [h 1;h 2;:::;h L] where h i is the output produced by the first LSTM after the ith word. The dataset consists of over 400,000 pairs of questions and corresponding labels indicating whether the two questions in a pair have the same intent. Quora Insincere Questions classification was the second kaggle competition hosted by quora with the objective to develop more scalable methods to detect toxic and misleading content on their platform. Siamese-LSTM Using MaLSTM model(Siamese networks + LSTM with Manhattan distance) to detect semantic similarity between question pairs. 63% of the questions pairs are semantically non-similar and 37% are duplicate questions pairs. There were around 400K question pairs in the training set while the testing set contained around 2. id: unique identifier for the question pair (unused) qid1: unique identifier for the first question (unused) qid2: unique identifier for the second question (unused). The term 'Siamese twins' derives from Chang and Eng Bunker (1811-1874) who were the first pair of conjoined twins to become internationally known. Developed by Daniel Falbel, JJ Allaire, François Chollet, RStudio, Google. Thanks for contributing an answer to Web Applications Stack Exchange! Please be sure to answer the question. edu Aniket Shenoy [email protected] After you complete this project, you can read about Quora’s approach to this problem in this blog post. 1109/APSIPA. The dataset consists of ~400k pairs of questions and a column indicating if the question pair is duplicated. The second question was then fed into the second LSTM and let h N be the final output vector of the second LSTM. Moreover, they also started Kaggle competition based on that dataset. The model architecture is based on the Stanford Natural Language Inference [2] benchmark model developed by Stephen Merity [3], specifically the version using a simple summation of GloVe word embeddings [4] to represent each question in the pair. 55 BiMPM 88. It includes 404351 question pairs with a label column indicating if they are duplicate or not. I have built a LSTM model to predict duplicate questions on the Quora official dataset. Siamese Manhattan LSTM for quora similar question-pair checking. A Keras model that addresses the Quora Question Pairs [1] dyadic prediction task. Implementation details. text_explanation_lime: How to use lime to explain text data. 1 Dataset We evaluated our models on the Quora question paraphrase dataset which contains over 404,000 question pairs with binary labels. Question 1, question 2: The actual textual contents of the questions. from both directions of question pairs. com) is a community-driven question and answer website where users, either anonymously or publicly, ask and answer questions. 55 BiMPM 88. Last active Apr 8, 2018. His simple model composed of one layer of convolution achieved excellent results on. py On first execution, this will download the required Quora and GloVe datasets and generate files that cache the training data and related word count and embedding data for subsequent runs. I have built a LSTM model to predict duplicate questions on the Quora official dataset. 8630 auc test. In this work, we propose a bilateral multi-perspective matching (BiMPM) model. Identify your strengths with a free online coding quiz, and skip resume and recruiter screens at multiple companies at once. In this project, we focus on a dataset published by Quora. 1 LSTM + GRU (Baseline) We reimplement a LSTM + GRU model has been shown to perform well for this task [1]. The data used in the Quora Question Pair Dataset is as in the Figure 1, There are ~404K Question Pairs like above for Training. 649 Table 3: Performance on Mohler CS dataset with 12-fold training (lower is better for RMSE and MAE; higher is better for. After you complete this project, you can read about Quora’s approach to this problem in this blog post. Take Quora Question Pairs dataset [15] as an instance: input data question 1 and question Siamese-CNN 79. Siamese LSTM for evaluating semantic similarity between sentences of the Quora Question Pairs Dataset. A screenshot of a Quora question asking why there are so many duplicate questions on Quora, which itself has been merged with a duplicate of itself. 1 indicates the question pair is duplicate. We also observe that using question-question pairs in our hybrid network, results in marginally better performance than using question-to-answer pairs. Quora Question Pair dataset is collected from the real-world questions on Quora website. Quora Question Pairs (Sep 2017-On Going) Classify Quora Questions into duplicate and non-duplicate categories. CNN, and BERT + Linear. The dataset first appeared in the Kaggle competition Quora Question Pairs and consists of approximately 400,000 pairs of questions along with a column indicating if the question pair is considered a duplicate. We had counts of neighbors of question 1, question 2, the min, the max, intersections, unions, shortest path length when main edge cut…. $ python3 keras-quora-question-pairs. It seems that you are referring to the sentence similarity model by Mueller and Thyagarajan (2016) [1]. from both directions of question pairs. In this post, I tackle the problem of classifying questions pairs based on whether they are duplicate or not duplicate. Developed by Daniel Falbel, JJ Allaire, François Chollet, RStudio, Google. CS224N Project: Natural Language Inference for Quora Dataset Kuy Hun Koh Yoo Energy Resources Engineering ory (LSTM) cells were applied to identify duplicate question-pairs in the Quora dataset. The Quora dataset is developed for paraphrase identification (to detect duplicate questions). The test labels are 0 or 1. cnAbstract There are two major problems in duplicate question identifi-. Detect toxic content to improve online conversations. I will do my best to explain the network and go through the Keras code (if you are only here for the code, scroll down :) Full…. Siamese neural network based on the long short-term memory (LSTM) [3] to model the sentences and measure the similarity between two sentences. Elior Cohen This article is about the MaLSTM Siamese LSTM network (link to article on the second paragraph) for sentence similarity and its appliance to Kaggle’s Quora Pairs competition. The dataset first appeared in the Kaggle competition Quora Question Pairs. In this iteration I first attempt to use word2vec embeddings, then bert embedings, and finally training embeddings with the model. We propose a novel approach of Siamese LSTM Net-work, which learns long term dependencies and capture sequential patterns present in the question and its related question, which was missing in the T-SCQA [15]. In this competition, Kagglers are challenged to tackle this natural language processing problem by applying advanced techniques to classify whether question pairs are duplicates or not. Used Manhattan LSTM to predict semantic similarity of two query phrases; Google word2vec was used to generate embeddings of query phrases; Achieved an accuracy of 80. ,2015), SICK (Marelli et al. I will do my best to explain the network and go through the Keras code (if you are only here for the code, scroll down :) Full code on Github In. I would like to train multiple models on the same data using Keras, as an exercise for me to get acquainted with hyperparameter tuning in Keras for R (in Python, I use a different approach based on the Python library hyp…. Detect toxic content to improve online conversations. 00238 and 0. The results on Quora and SemEval question similarity datasets show that NNs trained with our approach can learn more. 유사한 질문을 찾아내는 알고리즘을 고민하고 있던 중 Kaggle에서 Quora의 유사 질문을 찾는 Quora Question Pairs Competition을 알게 되었고, 여기에서 평가가 매우 좋은 Siamese LSTM 네트워크를 이용한 문장의 의미론적 유사도를 판별하는 논문을 살펴보고 구현을 진행해보았습니다. The problem at hand is to check whether a pair of questions posted on Quora website are similar or not. python keras Siamese LSTM Manhattan LSTM MaLSTM Semantic. text #Prepare embedding of the data — I am using quora question pairs for dataset in. There were around 400K question pairs in the training set while the testing set contained around 2. edu Abstract This paper presents a system which uses a combination of multiple text similarity measures of varying complexities to clas-sify Quora question pairs as duplicate or different. 522 12 LSTM All Avg SVOR LSTM-AvgPool-SVOR 0. edu Abstract We explored two approaches based on Long Short-Term Memory (LSTM) networks on the Quora duplicate question dataset. It's free, confidential, includes a free flight and hotel, along with help to study to pass interviews and negotiate a high salary!. I have used quora-questions pairs dataset and generated their embeddings using google-bert. com ### Daniel Falbel (@Curso-R e @Curso-R e > Quora Moment Generating Function Explained 2020-05-03 Quora Moment Generating Function Explained Moment Generating Function Explained - Towards Data Science Moment Generating Function Explained - Towards Data Science Moment generating function & bernoulli experiment. The dataset first appeared in the Kaggle competition Quora Question Pairs and consists of approximately 400,000 pairs of questions along with a column indicating if the question pair is considered a duplicate. In this competition, Kagglers are challenged to tackle this natural language processing problem by applying advanced techniques to classify whether question pairs are duplicates or not. Natural language sentence matching is a fundamental technology for a variety of tasks. View Aman Singh Verma's profile on LinkedIn, the world's largest professional community. 35% on Quora Question Pairs Dataset; Semantic similarity between current sentence and sentences in the corpus was used for. Now, i want to create a LSTM model like the above examples and use it but i am getting the following error: Using TensorFlow backend. In these blog posts series, I’ll describe my experience getting hands-on experience participating in it. Question semantic similarity is a challenging and active research problem that is very useful in many NLP applications, such as detecting duplicate questions in community question answering platforms such as Quora. ) The two LSTMs convert the variable length sequence into a fixed dimensional vector embedding. 8 MSEM (-multi-task) 88. Previous researches regard such problem as question matching task: given a pair of questions, the supervised models learn question representation and predict it similar or not. quora/question-pairs-dataset. The private leaderboard is calculated with approximately 94% of the test data. Detect toxic content to improve online conversations. • Trained a Siamese LSTM network and achieved close to state of the art accuracy of 84%. We trained our own word embeddings using Quora's text corpus, combined them to generate question embeddings for the two questions, and then fed those question embeddings into a representation layer. 8630 auc test. This data set is large, real, and relevant — a rare combination. As in case of. ,2015), SICK (Marelli et al. Implemented a Siamese LSTM model to identify similar questions from Quora based on their semantic similarity. We built density features from the graph built from the edges between pairs of questions inside train and test datasets concatenated. 18+ ] LSTM with GloVe and magic features. The model architecture is based on the Stanford Natural Language Inference [2] benchmark model developed by Stephen Merity [3], specifically the version using a simple summation of GloVe word embeddings [4] to represent each question in the pair. In this post, I like to investigate this dataset and at least propose a baseline method with deep learni. The first question was fed into the first LSTM, and its final hidden state was used as the first hidden state in the second LSTM. [Mueller and Thyagarajan, 2016] used Siamese LSTMs for NLI. Duplicate Questions Pair Detection Using Siamese MaLSTM Abstract: Quora is a growing platform comprising a user generated collection of questions and answers. [14] introduced a Con-. Investigating Siamese LSTM networks for text categorization @article{Shih2017InvestigatingSL, title={Investigating Siamese LSTM networks for text categorization}, author={Chin-Hong Shih and Bi-Cheng Yan and Shih-Hung Liu and Berlin Chen}, journal={2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. A screenshot of a Quora question asking why there are so many duplicate questions on Quora, which itself has been merged with a duplicate of itself. The final hidden states of each LSTM are combined by an element-wise multiplication. Designing an Automated Question-Answering System - Part III The idea is to train a LSTM model with tagged pair of questions and then use the weights learnt by the hidden layers of the network to generate vector representations for questions. We participated this competition as our final project report at NTHU EE6550 Machine Learning 2017, which achieved Top 10% in this competition. I have updated the question with brief dataset description and the goal of the model. Manhattan LSTM model for text similarity. The second question was then fed into the second LSTM and let h N be the final output vector of the second LSTM. Elior Cohen This article is about the MaLSTM Siamese LSTM network (link to article on the second paragraph) for sentence similarity and its appliance to Kaggle’s Quora Pairs competition. It falls under the category of the Binary Classification Problem. Siamese Manhattan LSTM for quora similar question-pair checking. is_duplicate: Label is 0 for questions which are semantically different and 1 for questions which essentially would have only one answer (duplicate questions). predict on the test data. QQP The Quora Question Pairs (QQP) dataset is a collection of question pairs from the community question-answering website Quora (Wang et al. 16 which placed us 3rd in class. For this purpose, the authors present a subset of Quora data that consists of over 400,000 question pairs. - Received a log loss of 0. The model achieved an accuracy of 80% on test data. Let Y = [h 1;h 2;:::;h L] where h i is the output produced by the first LSTM after the ith word. Cat Carrier (Siamese). In this iteration I first attempt to use word2vec embeddings, then bert embedings, and finally training embeddings with the model. We use the data split provided in Wang et al. In this project, the dataset consisted of different pairs of questions that were asked on the Quora Platform together with a class label that indicates whether the given pair are similar to each other. 1 Neural Network Architecture Kim trained a simple CNN on top of pre-trained word vectors for the sentence. In our experiments, we evaluate our model on 50K, 100K and 150K training dataset sizes. Currently, Quora uses a Random Forest model to identify duplicate questions. were input to a multi-layer LSTM-RNN architecture that out-puts one of the above classes. They propose a generic framework for For instance,Mueller and Thyagara-jan(2016) propose a siamese recurrent architec-ture using Manhattan LSTM (MaLSTM) for STS. Making statements based on opinion; back them up with references or personal experience. The first question was fed into the first LSTM, and its final hidden state was used as the first hidden state in the second LSTM. Training dataset used is a subset of the original Quora Question Pairs Dataset(~363K pairs used). Quora Which is a Question Answering company has this problem in the context of duplicate questions. Home Installation Tutorials Guide Deploy Tools API Learn Blog. Conventionally, neural methodology aligns the sentence pair and then generates a matching score for paraphrase identification, [18, 19]. Quora Question Pairs (Sep 2017-On Going) Classify Quora Questions into duplicate and non-duplicate categories. Siamese Manhattan LSTM for quora similar question-pair checking. Implemented a Siamese LSTM model to identify similar questions from Quora based on their semantic similarity. Manhattan LSTM Model The proposed Manhattan LSTM (MaLSTM) model is out-lined in Figure 1. Elior Cohen This article is about the MaLSTM Siamese LSTM network (link to article on the second paragraph) for sentence similarity and its appliance to Kaggle’s Quora Pairs competition. 3 Experiments 3. 2017;Tien et al. For these Question Pairs, I check of the length distribution of the Questions and as we see in Figure 2, both Question1 and Question2 have a similar distribution. Good luck!. atively few pairs of questions (few thou-sands) as gold standard (GS) training data is typically scarce, (ii) predicting labels on a very large corpus of question pairs, and (iii) pre-training NNs on such large cor-pus. 60 Siamese-LSTM 82. [13] combined a stack of character-level bidirectional LSTM with Siamese architec-ture to compare the relevance of two words or phrases. The problem of question pairs matching aims to seek whether the underlying semantics of two questions are equivalent. 522 12 LSTM All Avg SVOR LSTM-AvgPool-SVOR 0. Wang et al. cnAbstract There are two major problems in duplicate question identifi-. I have used quora-questions pairs dataset and generated their embeddings using google-bert. There are a total of 155 K such questions. Moreover, identifying questions with the same semantic content could help web-scale question answering systems that are increasingly concentrating on retrieving focused answers to users’ queries. Last active Apr 8, 2018. The second question was then fed into the second LSTM and let h N be the final output vector of the second LSTM. For this purpose, the authors present a subset of Quora data that consists of over 400,000 question pairs. There are a total of 155 K such questions. Collectible Companions of Classic. !LSTM Figure 3 shows my LSTM model. We trained our own word embeddings using Quora's text corpus, combined them to generate question embeddings for the two questions, and then fed those question embeddings into a representation layer. In this work, we propose a bilateral multi-perspective matching (BiMPM) model. F IGURE 1 – Siamese CNN+LSTM to calculate the similarity of a pair of sentences. Natural language sentence matching is a fundamental technology for a variety of tasks. Thanks for contributing an answer to Web Applications Stack Exchange! Please be sure to answer the question. Identifying Quora question pairs having the same intent Shashi Shankar [email protected] The first question was fed into the first LSTM, and its final hidden state was used as the first hidden state in the second LSTM. Highlights from Machine Learning Research, Projects and Learning Materials. September 10, 2017 — 0 Comments. Experimental results show that our models can make full use of the semantic information of the text, and the F1 value in the dataset pro-vided by the CCKS2018 question-intention matching task is 0. py On first execution, this will download the required Quora and GloVe datasets and generate files that cache the training data and related word count and embedding data for subsequent runs. ,2015), SICK (Marelli et al. cn Abstract. As Jupyter notebooks.