Schedule
- 9:00--9:15 - Opening Remarks
- 9:15--10:15 - Invited Talk (Chris Manning)
- 10:15--12:15 - Poster session 1
- A Simple Word Embedding Model for Lexical Substitution (Oren Melamud, Omer Levy and Ido Dagan)
- Unsupervised Text Normalization Using Distributed Representations of Words and Phrases (Vivek Kumar Rangarajan Sridhar)
- Combining Distributed Vector Representations for Words (Justin Garten, Kenji Sagae, Volkan Ustun and Morteza Dehghani)
- A Multi-classifier Approach to support Coreference Resolution in a Vector Space Model (Ana Zelaia, Olatz Arregi and Basilio Sierra)
- Neural context embeddings for automatic discovery of word senses (Mikael Kågebäck, Fredrik Johansson, Richard Johansson and Devdatt Dubhashi)
- Distributional Representations of Words for Short Text Classification (Chenglong Ma, Weiqun Xu, Peijia Li and Yonghong Yan)
- Relation Extraction: Perspective from Convolutional Neural Networks (Thien Huu Nguyen and Ralph Grishman)
- Distributional Semantic Concept Models for Entity Relation Discovery (Jay Urbain, Glenn Bushee and George Kowalski)
- A Deep Architecture for Non-Projective Dependency Parsing (Erick Fonseca and Sandra Aluisio)
- Short Text Clustering via Convolutional Neural Networks (jiaming xu, peng wang, guanhua tian, bo xu, jun zhao, fangyuan wang and hongwei hao)
- A Word-Embedding-based Sense Index for Regular Polysemy Representation (Marco Del Tredici and Nuria Bel)
- Simple Semi-Supervised POS Tagging (Karl Stratos and Michael Collins)
- Estimating User Location in Social Media with Stacked Denoising Auto-encoders (Ji Liu and Diana Inkpen)
- 12:15--13:30 - Lunch
- 13:30--14:30 - Paper Talks (Mohit Bansal, Karl Stratos, Gerard de Melo)
- 14:30--16:30 - Poster session 2
- Dependency Link Embeddings: Continuous Representations of Syntactic Substructures (Mohit Bansal)
- DeepNL: a Deep Learning NLP pipeline (Giuseppe Attardi)
- Unsupervised Topic Modeling for Short Texts Using Distributed Representations of Words (Vivek Kumar Rangarajan Sridhar)
- A Vector Space Approach for Aspect Based Sentiment Analysis (Abdulaziz Alghunaim, Mitra Mohtarami, Scott Cyphers and Jim Glass)
- Word Embeddings vs Word Types for Sequence Labeling: the Curious Case of CV Parsing (Melanie Tosik, Carsten Lygteskov Hansen, Gerard Goossen and Mihai Rotaru)
- Morpho-syntactic Regularities in Continuous Word Representations: A multilingual study (Garrett Nicolai, Colin Cherry and Grzegorz Kondrak)
- Towards Combined Matrix and Tensor Factorization for Universal Schema Relation Extraction (Sameer Singh, Tim Rocktaschel and Sebastian Riedel)
- Neural word embeddings with multiplicative feature interactions for tensor-based compositions (Joo-Kyung Kim, Marie-Catherine de Marneffe and Eric Fosler-Lussier)
- Bilingual Word Representations with Monolingual Quality in Mind (Thang Luong, Hieu Pham and Christopher D. Manning)
- Learning Distributed Representations for Multilingual Text Sequences (Hieu Pham, Thang Luong and Christopher Manning)
- Distributed Word Representations Improve NER for e-Commerce (Mahesh Joshi, Ethan Hart, Mirko Vogel and Jean-David Ruvini)
- Semantic Information Extraction for Improved Word Embeddings (Jiaqiang Chen and Gerard de Melo)
- Named Entity Recognition for Arabic Social Media (Ayah Zirikly and Mona Diab)
- Vector Space Models for Scientific Document Summarization (John Conroy and Sashka Davis)
- 16:30--17:30 - Invited Talk (Marco Baroni)
- 17:30--17:45 - Concluding Remarks and Best Paper Award (to Jiaqiang Chen and Gerard de Melo for ``Semantic Information Extraction for Improved Word Embeddings'')
- 17:45--19:00 - Farewell Reception