Deep Learning for Question Answering

This posting presents recent publications related to Deep Learning for Question Answering. Question Answering is described as “a computer science discipline within the fields of information retrieval and natural language processing (NLP), which is concerned with building systems that automatically answer questions posed by humans in a natural language”. I’ll also publish postings about Deep Learning for Information Retrieval and Learning to Rank today.

Best regards,
Amund Tveit

Year  Title Author
2016   Skipping Word: A Character-Sequential Representation based Framework for Question Answering  L Meng, Y Li, M Liu, P Shu
2016   Semantic computation in geography question answering  S Zhao, Y Zheng, C Zhu, T Zhao, S Li
2016   Open-ended visual question answering  I Masuda Mora
2016   Creating Causal Embeddings for Question Answering with Minimal Supervision  R Sharp, M Surdeanu, P Jansen, P Clark, M Hammond
2016   Deep Feature Fusion Network for Answer Quality Prediction in Community Question Answering  SP Suggu, KN Goutham, MK Chinnakotla
2016   ECNU at SemEval-2016 Task 3: Exploring traditional method and deep learning method for question retrieval and answer ranking in community question answering  G Wu, M Lan
2016   Ask Your Neurons: A Deep Learning Approach to Visual Question Answering  M Malinowski, M Rohrbach, M Fritz
2016   Revisiting Visual Question Answering Baselines  A Jabri, A Joulin, L van der Maaten
2016   End to End Long Short Term Memory Networks for Non-Factoid Question Answering  D Cohen, WB Croft
2016   Question Answering on Linked Data: Challenges and Future Directions  S Shekarpour, D Lukovnikov, AJ Kumar, K Endris
2016   Extracting Medical Knowledge from Crowdsourced Question Answering Website  Y Li, C Liu, N Du, W Fan, Q Li, J Gao, C Zhang, H Wu
2015   Building a Large-scale Multimodal Knowledge Base for Visual Question Answering  Y Zhu, C Zhang, C Ré, L Fei
2015   Answer Sequence Learning with Neural Networks for Answer Selection in Community Question Answering  X Zhou, B Hu, Q Chen, B Tang, X Wang
2015   Empirical Study on Deep Learning Models for Question Answering  Y Yu, W Zhang, CW Hang, B Zhou
2015   Simple Baseline for Visual Question Answering  B Zhou, Y Tian, S Sukhbaatar, A Szlam, R Fergus
2015   Chess Q&A: Question Answering on Chess Games  V Cirik, LP Morency, E Hovy
2015   Predicting the Quality of User-Generated Answers Using Co-Training in Community-based Question Answering Portals  B Liu, J Feng, M Liu, H Hu, X Wang
2015   Open Domain Question Answering via Semantic Enrichment  H Sun, H Ma, W Yih, CT Tsai, J Liu, MW Chang
2015   Visual Question Answering using Deep Learning  S Agrawal, A Mukherjee
2015   Learning Semantic Representation with Neural Networks for Community Question Answering Retrieval  G Zhou, Y Zhou, T He, W Wu
2015   WIKIQA: A Challenge Dataset for Open-Domain Question Answering  Y Yang, W Yih, C Meek
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Deep Learning for Sentiment Analysis

Recently I published Embedding for NLP with Deep Learning (e.g. word2vec and follow-ups) and Deep Learning for Natural Language Processing – ICLR 2017 Discoveries – this posting is also mostly NLP-related since it provides recent papers related to Deep Learning for Sentiment Analysis, but also has examples of other types of sentiment (e.g. image sentiment).

Best regards,
Amund Tveit

Year  Title Author
2016   Image Sentiment Analysis using Deep Convolutional Neural Networks with Domain Specific Fine Tuning  S Jindal, S Singh
2016   Multi-Objective Model Selection (MOMS)-based Semi-Supervised Framework for Sentiment Analysis  FH Khan, U Qamar, S Bashir
2016   Real-Time Topic and Sentiment Analysis in Human-Robot Conversation  E Russell
2016   Finki at SemEval-2016 Task 4: Deep Learning Architecture for Twitter Sentiment Analysis  D Stojanovski, G Strezoski, G Madjarov, I Dimitrovski
2016   Design of Sentiment Analysis System for Hindi Content  M Yadav, V Bhojane
2016   Visual Sentiment Analysis for Social Images Using Transfer Learning Approach  J Islam, Y Zhang
2016   Unsupervised Feature Learning Assisted Visual Sentiment Analysis  Z Li, Y Fan, F Wang, W Liu
2016   Context-Aware Text Representation for Social Relation Aided Sentiment Analysis  LM Nguyen
2016   Select-Additive Learning: Improving Cross-individual Generalization in Multimodal Sentiment Analysis  H Wang, A Meghawat, LP Morency, EP Xing
2016   A semi-supervised approach to sentiment analysis using revised sentiment strength based on SentiWordNet  FH Khan, U Qamar, S Bashir
2016   SWIMS: Semi-Supervised Subjective Feature Weighting and Intelligent Model Selection for Sentiment Analysis  FH Khan, U Qamar, S Bashir
2016   Cross-modality Consistent Regression for Joint Visual-Textual Sentiment Analysis of Social Multimedia  Q You, J Luo, H Jin, J Yang
2016   INSIGHT-1 at SemEval-2016 Task 5: Deep Learning for Multilingual Aspect-based Sentiment Analysis  S Ruder12, P Ghaffari, JG Breslin
2016   SENSEI-LIF at SemEval-2016 Task 4: Polarity embedding fusion for robust sentiment analysis  M Rouvier, B Favre
2016   Leveraging Multimodal Information for Event Summarization and Concept-level Sentiment Analysis  RR Shah, Y Yu, A Verma, S Tang, AD Shaikh
2016   Visual and Textual Sentiment Analysis of a Microblog Using Deep Convolutional Neural Networks  Y Yu, H Lin, J Meng, Z Zhao
2016   Sentiment Analysis for Chinese Microblog based on Deep Neural Networks with Convolutional Extension Features  SUN Xiao, LI Chengcheng, REN Fuji
2016   PotTS at SemEval-2016 Task 4: Sentiment Analysis of Twitter Using Character-level Convolutional Neural Networks.  U Sidarenka, KL Straße
2016   Recursive Neural Conditional Random Fields for Aspect-based Sentiment Analysis  W Wang, SJ Pan, D Dahlmeier, X Xiao
2016   eSAP: A Decision Support Framework for Enhanced Sentiment Analysis and Polarity Classification  FH Khan, U Qamar, S Bashir
2016   Paragraph2Vec-based sentiment analysis on social media for business in Thailand  P Sanguansat
2016   Sentiment Analysis of Chinese Micro Blog Based on DNN and ELM and Vector Space Model  H Liu, S Li, C Jiang, H Liu
2016   Sentiment Analysis in Finance Market Forcast  D Wang
2016   Visual Sentiment Analysis with Network in Network  Z Li, Y Fan, F Wang
2015   Convolutional Neural Networks for Multimedia Sentiment Analysis  G Cai, B Xia
2015   Sentiment Analysis with Incremental Human-in-the-Loop Learning and Lexical Resource Customization  S Mishra, J Diesner, J Byrne, E Surbeck
2015   Parallel Recursive Deep Model for Sentiment Analysis  G Tian, Y Zhou
2015   Unsupervised Sentiment Analysis for Social Media Images  Y Wang, S Wang, J Tang, H Liu, B Li
2015   Prediction of changes in the stock market using twitter and sentiment analysis  IV Serban, DS González, X Wu
2015   Review Sentiment Analysis Based on Deep Learning  Z Hu, J Hu, W Ding, X Zheng
2015   Twitter Sentiment Analysis Using Deep Convolutional Neural Network  D Stojanovski, G Strezoski, G Madjarov, I Dimitrovski
2015   Sentiment-Specific Representation Learning for Document-Level Sentiment Analysis  D Tang
2015   Sentiment Analysis via Integrating Distributed Representations of Variable-length Word Sequence  Z Cui, X Shi, Y Chen
2015   Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis  T Huynh, Y He, S Rüger
2015   Recursive Autoencoder with HowNet Lexicon for Sentence-Level Sentiment Analysis  X Fu, Y Xu
2014   Recursive Deep Learning for Sentiment Analysis over Social Data  C Li, B Xu, G Wu, S He, G Tian, H Hao
2014   Robust Image Sentiment Analysis Using Progressively Trained and Domain Transferred Deep Networks  Q You, J Luo, H Jin, J Yang
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