Answers and Wikipedia, which are at a low ebb, social question answering sites, including Quora and Zhihu, are gaining momentum. For triplet loss the net-work is trained with margin = 0:5. 65k. Short hands-on challenges to perfect your data manipulation skills. Version 1.1 released August 6, 2010 README.v1.1; Question_Answer_Dataset_v1.1.tar.gz; Version 1.0 released February 18, 2010 … the Quora dataset and 10,000 bins for the QA dataset. Manually … RNN seems the best model on Insurance-QA dataset. Successive words from Google books. Maluuba goal-oriented dialogue: Procedural conversational dataset where the dialogue aims at accomplishing a … Multiple questions with the same … (2016) consider a related … Machine Learning. We train and test the models with a subset of the Quora duplicate questions dataset in the medical area. CMU Q/A Dataset: Manually-generated factoid question/answer pairs with difficulty ratings from Wikipedia articles. Quora Question Pairs. RNN seems the best model on Insurance-QA dataset. such as Stack Exchange and Quora and from collections like TREC-QA rarely contain questions with a combina-tion of text and images. Project idea – This is an interesting machine learning project. Learn the most important language for Data Science. It consists of 5,957 multiple-choice elementary-level science questions (4,957 train, 500 dev, 500 test), which probe the understanding of a small “book” of 1,326 core science facts and the application of these facts to novel situations. This is a repo for Q&A Mathing, includes some deep learning models, such as CNN、RNN. import os: os. CNN. … for this it uses principles from Natural language processing and Information retrieval. Basic CNN model from 《Applying Deep Learning To Answer Selection: A Study And An Open Task》 RNN. – Quora @pskomoroch #dataset – Delicious Free, Public Data Sets | Hacker News List of European Open Data Catalogues at Open Data Datasets Archive Some Datasets Available on the Web » Data Wrangling Blog. to find the most similar question from a large QA dataset. No Active Events. The dataset now includes 10,898 articles, 17,794 tweets, and 13,757 crowdsourced question-answer pairs. question answering. 65k. Basic CNN model from 《Applying Deep Learning To Answer Selection: A Study And An Open Task》 RNN. Got it. Yahoo Language Data: This page features manually curated QA datasets from Yahoo Answers from Yahoo. Maluuba News QA Dataset. 114 lines (84 sloc) 3.93 KB Raw Blame. Text . It is the only dataset which provides sentence-level and word-level answers at the same time. In this work, we use data from Ya-hoo! Owned. search. length of the train = ( speed x time ) . 2 Related Work Paraphrase identication is a well-studied task in NLP (Das and Smith,2009;Chang et al.,2010;He et al.,2015;Wang et al.,2016, inter alia). We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. Quora Question Pairs: first dataset release from Quora containing duplicate / semantic similarity labels. In each track, the task was defined such that the systems were to retrieve small snippets of text that contained an answer for open-domain, closed-class questions. clear. Catching Illegal Fishing Project. 3 Making a Long Form QA Dataset 3.1 Creating the Dataset from ELI5 There are several websites which provide forums to ask open-ended questions such as Yahoo An-swers, Quora, as well as numerous Reddit forums, or subreddits. 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). Upvoted. … auto_awesome_motion. CSV Dataset | 546 upvotes. We compare HBAM with other state-of-the-art language models such as bidirectional encoder representation from transformers (BERT) and Manhattan LSTM Model (MaLSTM). question answering. JAPAN’s community QA website Yahoo! CMU Q/A Dataset. 3 Problem Setup We seek to understand how to best transfer relevant knowledge to a general language model for medical question similarity. TWEETQA is a social media-focused question answering dataset. Manually, you can use [code ]pd.DataFrame[/code] constructor, giving a numpy array ([code ]data[/code]) and a list of the names of the columns ([code ]columns[/code]). There are many ships, boats on the oceans and it is impossible to manually keep track of what everyone is doing. • Rationale: Speed = ( 48 x 5 / 18 ) m / sec = ( 40 / 3 ) m / sec . Dataset: Speech Emotion Recognition Dataset. Deep Learning. However, since the test set is typically a randomly selected subset of the whole set of data collected, and thus follows the same distribution as the training and development sets, the perfor-mance of models on the test set tends to overes-timate the models’ … OpenBookQA is a new kind of question-answering dataset modeled after open book exams for assessing human understanding of a subject. Our first dataset is related to the problem of identifying duplicate questions. We focus on the subreddit Explain Like I’m Five (ELI5) where users are encouraged to provide answers which are comprehensible by a five year old.3 ELI5 is appealing … By using Kaggle, you agree to our use of cookies. Insurance-QA deeplearning model. Upvoted. For … It’s a platform to ask questions and connect with people who contribute unique insights and quality answers. CNN. Learn more. NarrativeQA is a data set constructed to encourage deeper understanding of language. what is the length of the train ? Our hypothesis is that by training on a large corpus for a similar medical task, we can embed medical knowledge into the model. The total number of medical related data from Quora dataset is nearly 70000, but we randomly pick the 10000 as the (train/dev/test) dataset. Best practices for creating a labeled dataset for ML: 1) Collect the dataset in tiers. Over 100 million people visit Quora every month, so it's no surprise that many people ask similarly worded questions. On the popular SQuAD dataset (Rajpurkar et al.,2016), top QA models have achieved higher evaluation scores compared to hu-man. I build a model based on Facebook AI's roBERTa base to classify questions on Quora as sincere or insincere. Create notebooks or datasets and keep track of their status here. Don’t collect/ label all of the data in one batch. Groups. Model Average Eval_accuracy by three times Range of change; BERT baseline model: 0.7686 (-0.0073, +0.0057) HDBA model: 0.8146 (-0.0082, +0.0098) Bi-LSTM + Attention model: 0.8043 (-0.0103, +0.0062) The scale of … QA systems. Besides interactions, the latter enables users to label the questions with topic tags that highlight the key points conveyed in the questions. Quora is a place to gain and share knowledge—about anything. Human evaluation indicate that the paraphrases generated by our system are well-formed, … Version 1.2 released August 23, 2013 (same data as 1.1, but now released under GFDL and CC BY-SA 3.0) README.v1.2; Question_Answer_Dataset_v1.2.tar.gz. The data set consists of 113,000 Wikipedia-based QA pairs.