The objective was to minimize the logloss of predictions on duplicacy in the testing dataset. % len(embeddings_index)), embedding_matrix = np.zeros((max_words, embedding_dim)), embedding_vector = embeddings_index.get(word), lstm_layer = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(lstm_units, dropout=0.2, recurrent_dropout=0.2)), mhd = lambda x: tf.keras.backend.abs(x[0] - x[1]), history = model.fit([x_train[:,0], x_train[:,1]], y_train, epochs=100, validation_data=([x_val[:,0], x_val[:,1]], y_val)), https://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/download/12195/12023, Noam Chomsky on the Future of Deep Learning, A Full-Length Machine Learning Course in Python for Free, An end-to-end machine learning project with Python Pandas, Keras, Flask, Docker and Heroku, Ten Deep Learning Concepts You Should Know for Data Science Interviews, Kubernetes is deprecating Docker in the upcoming release. Each line contains IDs for each question in the pair, the full text for each question, and a binary value that indicates whether the line truly contains a duplicate pair. So, for our study, we choose all such question pairs with binary value 1. Take a look, question1, question2, labels = load_data(df), return ''.join(i for i in text if ord(i) < 128), # Padding sequences to a max embedding length of 100 dim and max len of the sequence to 300, sequences = tok.texts_to_sequences(combined)sequences = pad_sequences(sequences, maxlen=300, padding='post'), coefs = np.asarray(values[1:], dtype='float32'), print('Found %s word vectors.' Dataset. © 2020 Forbes Media LLC. “First Quora Dataset Release: Question Pairs,” 24 January 2016. done. 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. First we build a Tokenizer out of all our vocabulary. First Quora Dataset Release: Question Pairs originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world. Each line contains IDs for each question in the pair, the full text for each question, and a binary value that indicates whether the line truly contains a duplicate pair. Shankar Iyar, Nikhil Dandekar, and Kornél Csernai. We split the data randomly into 243k train examples, 80k dev examples, and 80k test examples. Ever wondered how to calculate text similarity using Deep Learning? the opportunity to try their hand at some of the challenges that arise in building a scalable online knowledge-sharing platform. Our dataset consists of over 400,000 lines of potential question duplicate pairs. 1.2 This Work. The data, made available for non-commercial purposes (https://www.quora.com/about/tos) in a Kaggle competition (https://www.kaggle.com/c/quora-question-pairs) and on Quora’s blog (https://data.quora.com/First-Quora-Dataset-Release-Question-Pairs), consists of 404,351 question pairs with 255,045 negative samples (non-duplicates) and 149,306 positive sa… Datasets We evaluate our models on the Quora question paraphrase dataset which contains over 400K question pairs with binary labels. License. We use the MSE as our loss function and an Adam optimizer. SambitSekhar • updated 4 years ago (Version 1) Data Tasks Notebooks (18) Discussion Activity Metadata. References. I also had to correct a few minor problems with the TSV formatting (essentially, some questions contained new lines when shouldn’t have, which upset Python’s csv modul… SQuAD was created by getting crowd workers stand and reason and also enable knowledge-seekers on forums or question and answer platforms to more efficiently learn and read. First Quora Dataset Release: Question Pairs Authors: Shankar Iyer , Nikhil Dandekar , and Kornél Csernai Today, we are excited to announce the first in what we plan to be a series of public dataset releases. We use an LSTM layer to encode our 100 dim word embedding. Our dataset consists of: id: The ID of the training set of a pair; qid1, qid2: Unique ID of the question; question1: Text for Question One; question2: Text for Question Two; is_duplicate: 1 if question1 and question2 have the same meaning or else 0 We will be using the Quora Question Pairs Dataset. Therefore, we supplemented the dataset with negative examples. Meta. This data set is large, real, and relevant — a rare combination. To train our model, we simply call the fit function followed by the inputs. Python Alone Won’t Get You a Data Science Job. Hands-on real-world examples, research, tutorials, and cutting-edge techniques delivered Monday to Thursday. This is a challenging problem in natural language processing and machine learning, and it is a problem for which we are always searching for a better solution. Our original sampling method returned an imbalanced dataset with many more true examples of duplicate pairs than non-duplicates. MIT. 6066 be improved for better reliability of QA models on unseen test questions. the place to gain and share knowledge, empowering people to learn from others and better understand the world. Yeah, 2.5 million! Our first dataset is related to the problem of identifying duplicate questions. Our dataset consists of over 400,000 lines of potential question duplicate pairs. After Config description: The Stanford Question Answering Dataset is a question-answering dataset consisting of question-paragraph pairs, where one of the sentences in the paragraph (drawn from Wikipedia) contains the answer to the corresponding question (written by an annotator). The goal is to predict which of the included question pairs contain pairs having identical meanings. Research questions one and two have been studied on the first dataset released by Quora. L et us first start by exploring the dataset. Having a canonical page for each logically distinct query makes knowledge-sharing more efficient in many ways: for example, knowledge seekers can access all the answers to a question in a single location, and writers can reach a larger readership than if that audience was divided amongst several pages. You can follow Quora on Twitter, Facebook, and Google+. We aim to develop a model to detect text similarity between texts. As a simple example, the queries “What is the most populous state in the USA?” and “Which state in the United States has the most people?” should not exist separately on Quora because the intent behind both is identical. One source of negative examples were pairs of “related questions” which, although pertaining to similar topics, are not truly semantically equivalent. Wherever the binary value is 1, the question in the pair are not identical; they are rather paraphrases of each-other. We are eager to see how diverse approaches fare on this problem. You may opt-out by. In our model, we will use an embedding matrix developed using Glove weights and take word vectors for each of our sentence. There are a total of 155 K such questions. Classification, regression, and prediction — what’s the difference? Each record in the training set represents a pair of questions and a binary label indicating if it is a duplicate or not. We focus on the SQuAD QA task in this paper. We split the data into 10K pairs each for development and test, and the rest for training. Quora question pairs train set contained around 400K examples, but we can get pretty good results for the dataset (for example MRPC task in GLUE) with less than 5K examples also. 4.3. Dataset. Finding an accurate model that can determine if two questions from the Quora dataset are semanti- Introduction. Follow forum and comments . We have extracted different features from the existing question pair dataset and applied various machine learning techniques. Opinions expressed by Forbes Contributors are their own. It is released in the same manner as the AskUbuntuTO dataset. train.tsv/dev.tsv/test.tsv are our split of the original "Quora Sentence Pairs" dataset (https://data.quora.com/First-Quora-Dataset-Release-Question-Pairs). To validate the dataset’s labels, we did a blind test on 200 randomly sampled instances to see how well an First Quora Dataset Release: Question Pairs Quora Duplicate or not. Now we have created our embedding matrix, we will nor start building our model. Fast, efficient, open-access datasets and evaluation metrics in PyTorch, TensorFlow, NumPy and Pandas - huggingface/datasets This dataset is a portion with 30 K question pairs randomly extracted from the Quora dataset by . QQP The Quora Question Pairs2 dataset is a collection of question pairs from the community question-answering website Quora. The Quora dataset consists of a large number of question pairs and a label which mentions whether the question pair is logically duplicate or not. We will obtain the pre-trained model (https://nlp.stanford.edu/projects/glove/) and load it as our first layer as the embedding layer. In our experiments, we evaluate our model on 50K, 100K and 150K training dataset … Authors: Shankar Iyer, Nikhil Dandekar, and Kornél Csernai, on Quora: We are excited to announce the first in what we plan to be a series of public dataset releases. As our problem is related to the semantic meaning of the text, we will use a word embedding as our first layer in our Siamese Network. (1 refers to maximum similarity and 0 refers to minimum similarity). The data, made available for non-commercial purposes (https://www.quora.com/about/tos) in a Kaggle competition (https://www.kaggle.com/c/quora-question-pairs) and on Quora’s blog (https://data.quora.com/First-Quora-Dataset-Release-Question-Pairs) … Let us first start by exploring the dataset. An important product principle for Quora is that there should be a single question page for each logically distinct question. Now assuming, we have downloaded the Glove pre-trained vectors from here, we initialize our embedding layer with the embedding matrix. The file contains about 405,000 question pairs, of which about 150,000 are duplicates and 255,000 are distinct. We perform numerous experiments using Quora’s “Question Pairs” dataset,1which consists of 404,351 pairs of questions labeled as ‘duplicates’ or ‘not duplicates’. We convert the task into sentence pair classification by forming a pair between each question and each sentence in … First Quora Dataset Release: Question Pairs Quora Duplicate or not. Our dataset consists of: Like any Machine Learning project, we will start by preprocessing the data. The dataset used for this analysis was provided by Quora, released as their first public dataset as described above. It has disjoint 20 K, 1 K and 4 K question pairs for training, validation, and testing. The Keras model architecture is shown below: The model architecture is based on the Stanford Natural LanguageInference benchmarkmodel developed by Stephen Merity, specifically the versionusing a simple summation of GloVe word embeddingsto represent eachquestion in the pair. The distribution of questions in the dataset should not be taken to be representative of the distribution of questions asked on Quora. The task is to determine whether a pair of questions are seman-tically equivalent. “What is the most populous state in the USA?” This class imbalance immediately means that you can get 63% accuracy just by returning “distinct” on every record, so I decided to balance the two classes evenly to ensure that the classifier genuinely learnt something. The dataset that we are releasing today will give anyone the opportunity to train and test models of semantic equivalence, based on actual Quora data. 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