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1
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Syntactic topic models. Computational Linguistics
– J Boyd-Graber, D Blei
- 2008
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2
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NUS-ML:Improving word sense disambiguation using topic features
– Jun Fu Cai, Wee Sun Lee, Yee Whye Teh
- 2005
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8
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RACAI: Meaning Affinity Models
– Radu Ion
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2
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TKB-UO: Using Sense Clustering for WSD
– Henry Anaya-sánchez, Aurora Pons-porrata, Rafael Berlanga-llavori
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1
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Topic Model Analysis of Metaphor Frequency for Psycholinguistic Stimuli
– Steven Bethard, Vicky Tzuyin Lai, James H. Martin
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2
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07: Coarse-grained English allwords task
– SemEval-2007 Task
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3
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Contextual idiom detection without labelled data
– L Li, C Sporleder
- 2009
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9
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Snowball: A language for stemming algorithms. http://snowball.tartarus.org
– M F Porter
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16
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A Topic Model for Word Sense Disambiguation
– Jordan Boyd-Graber, et al.
- 2007
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24
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Syntactic Topic Models
– Jordan Boyd-graber, David Blei
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27
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A clustering approach for nearly unsupervised recognition of nonliteral language
– Julia Birke, Anoop Sarkar
- 2006
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152
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A General Language Model for Information Retrieval
– Fei Song, W. Bruce Croft
- 1999
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40
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Finding Predominant Word Senses in Untagged Text
– Diana Mccarthy, Rob Koeling, Julie Weeds, John Carroll
- 2004
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88
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Evaluating WordNet-based measures of lexical semantic relatedness
– Alexander Budanitsky, Graeme Hirst
- 2006
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10
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NUS-PT: Exploiting Parallel Texts for Word Sense Disambiguation in the English All-Words Tasks
– Yee Seng Chan, Hwee Tou Ng, Zhi Zhong
- 2007
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16
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Meaningful Clustering of Senses Helps Boost Word Sense Disambiguation Performance
– Roberto Navigli
- 2006
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41
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Automatic identification of non-compositional multi-word expressions using latent semantic analysis
– Graham Katz
- 2006
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1370
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Latent dirichlet allocation
– David M. Blei, Andrew Y. Ng, Michael I. Jordan, John Lafferty
- 2003
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545
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Probabilistic Latent Semantic Indexing
– Thomas Hofmann
- 1999
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