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Multi-Prototype Vector-Space Models of Word Meaning
Joseph Reisinger
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Raymond J. Mooney
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Paper Details:
Month: June
Year: 2010
Location: Los Angeles, California
Venue:
NAACL |
Citations
URL
A Probabilistic Model for Learning Multi-Prototype Word Embeddings
Fei Tian
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Hanjun Dai
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Jiang Bian
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Bin Gao
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Rui Zhang
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Enhong Chen
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Tie-Yan Liu
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Learning Sense-specific Word Embeddings By Exploiting Bilingual Resources
Jiang Guo
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Wanxiang Che
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Haifeng Wang
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Ting Liu
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Inducing Latent Semantic Relations for Structured Distributional Semantics
Sujay Kumar Jauhar
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Eduard Hovy
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Unsupervised Word Sense Induction using Distributional Statistics
Kartik Goyal
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Eduard Hovy
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Inducing Bilingual Lexica From Non-Parallel Data With Earth Mover’s Distance Regularization
Meng Zhang
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Yang Liu
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Huanbo Luan
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Yiqun Liu
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Maosong Sun
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Measuring Distributional Similarity in Context
Georgiana Dinu
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Mirella Lapata
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Polarity Inducing Latent Semantic Analysis
Wen-tau Yih
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Geoffrey Zweig
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John Platt
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Modeling and Learning Semantic Co-Compositionality through Prototype Projections and Neural Networks
Masashi Tsubaki
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Kevin Duh
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Masashi Shimbo
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Yuji Matsumoto
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Bilingual Word Embeddings for Phrase-Based Machine Translation
Will Y. Zou
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Richard Socher
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Daniel Cer
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Christopher D. Manning
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Multi-Relational Latent Semantic Analysis
Kai-Wei Chang
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Wen-tau Yih
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Christopher Meek
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A Unified Model for Word Sense Representation and Disambiguation
Xinxiong Chen
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Zhiyuan Liu
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Maosong Sun
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Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space
Arvind Neelakantan
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Jeevan Shankar
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Alexandre Passos
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Andrew McCallum
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Context-Dependent Sense Embedding
Lin Qiu
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Kewei Tu
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Yong Yu
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Vector-space models for PPDB paraphrase ranking in context
Marianna Apidianaki
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SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity
Daniela Gerz
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Ivan Vulić
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Felix Hill
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Roi Reichart
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Anna Korhonen
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Evaluating Distributional Models of Semantics for Syntactically Invariant Inference
Jackie Chi Kit Cheung
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Gerald Penn
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What Substitutes Tell Us - Analysis of an “All-Words” Lexical Substitution Corpus
Gerhard Kremer
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Katrin Erk
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Sebastian Padó
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Stefan Thater
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Measuring Word Meaning in Context
Katrin Erk
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Diana McCarthy
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Nicholas Gaylord
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A Rank-based Distance Measure to Detect Polysemy and to Determine Salient Vector-Space Features for German Prepositions
Maximilian Köper
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Sabine Schulte im Walde
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A comparison of models of word meaning in context
Georgiana Dinu
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Stefan Thater
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Soeren Laue
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Measuring Word Relatedness Using Heterogeneous Vector Space Models
Wen-tau Yih
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Vahed Qazvinian
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Combining Heterogeneous Models for Measuring Relational Similarity
Alisa Zhila
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Wen-tau Yih
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Christopher Meek
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Geoffrey Zweig
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Tomas Mikolov
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Supervised All-Words Lexical Substitution using Delexicalized Features
György Szarvas
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Chris Biemann
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Iryna Gurevych
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Modeling Word Meaning in Context with Substitute Vectors
Oren Melamud
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Ido Dagan
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Jacob Goldberger
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Ontologically Grounded Multi-sense Representation Learning for Semantic Vector Space Models
Sujay Kumar Jauhar
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Chris Dyer
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Eduard Hovy
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Sparse Bilingual Word Representations for Cross-lingual Lexical Entailment
Yogarshi Vyas
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Marine Carpuat
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K-Embeddings: Learning Conceptual Embeddings for Words using Context-Embeddings: Learning Conceptual Embeddings for Words using Context
Thuy Vu
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D. Stott Parker
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Bilingual Learning of Multi-sense Embeddings with Discrete Autoencoders
Simon Šuster
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Ivan Titov
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Gertjan van Noord
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Retrofitting Sense-Specific Word Vectors Using Parallel Text
Allyson Ettinger
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Philip Resnik
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Marine Carpuat
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Improving Word Representations via Global Context and Multiple Word Prototypes
Eric Huang
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Richard Socher
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Christopher Manning
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Andrew Ng
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Identifying Bad Semantic Neighbors for Improving Distributional Thesauri
Olivier Ferret
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A Two Level Model for Context Sensitive Inference Rules
Oren Melamud
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Jonathan Berant
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Ido Dagan
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Jacob Goldberger
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Idan Szpektor
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Question Answering Using Enhanced Lexical Semantic Models
Wen-tau Yih
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Ming-Wei Chang
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Christopher Meek
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Andrzej Pastusiak
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Resolving Lexical Ambiguity in Tensor Regression Models of Meaning
Dimitri Kartsaklis
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Nal Kalchbrenner
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Mehrnoosh Sadrzadeh
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Distributed Representations of Geographically Situated Language
David Bamman
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Chris Dyer
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Noah A. Smith
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SensEmbed: Learning Sense Embeddings for Word and Relational Similarity
Ignacio Iacobacci
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Mohammad Taher Pilehvar
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Roberto Navigli
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Unsupervised Person Slot Filling based on Graph Mining
Dian Yu
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Heng Ji
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Embeddings for Word Sense Disambiguation: An Evaluation Study
Ignacio Iacobacci
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Mohammad Taher Pilehvar
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Roberto Navigli
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Linear Algebraic Structure of Word Senses, with Applications to Polysemy
Sanjeev Arora
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Yuanzhi Li
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Yingyu Liang
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Tengyu Ma
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Andrej Risteski
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Regular polysemy: A distributional model
Gemma Boleda
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Sebastian Padó
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Jason Utt
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NTNU-CORE: Combining strong features for semantic similarity
Erwin Marsi
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Hans Moen
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Lars Bungum
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Gleb Sizov
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Björn Gambäck
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André Lynum
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A Hybrid Distributional and Knowledge-based Model of Lexical Semantics
Nikolaos Aletras
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Mark Stevenson
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Detecting Asymmetric Semantic Relations in Context: A Case-Study on Hypernymy Detection
Yogarshi Vyas
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Marine Carpuat
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Exemplar-Based Word-Space Model for Compositionality Detection: Shared Task System Description
Siva Reddy
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Diana McCarthy
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Suresh Manandhar
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Spandana Gella
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Towards Dynamic Word Sense Discrimination with Random Indexing
Hans Moen
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Erwin Marsi
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Björn Gambäck
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Better Word Representations with Recursive Neural Networks for Morphology
Thang Luong
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Richard Socher
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Christopher Manning
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Word Sense Filtering Improves Embedding-Based Lexical Substitution
Anne Cocos
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Marianna Apidianaki
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Chris Callison-Burch
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Implicit Subjective and Sentimental Usages in Multi-sense Word Embeddings
Yuqi Sun
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Haoyue Shi
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Junfeng Hu
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http://mturk.com
Field Of Study
Linguistic Trends
Lexical Semantics
Task
Word Sense Disambiguation
Semantic Similarity
Information Retrieval
Language
English
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