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PUTOP: Turning Predominant Senses into a Topic Model for Word Sense Disambiguation
Jordan Boyd-Graber
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David Blei
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Paper Details:
Month: June
Year: 2007
Location: Prague, Czech Republic
Venue:
*SEMEVAL |
SIG: SIGLEX
Citations
URL
Learning Word Sense Distributions, Detecting Unattested Senses and Identifying Novel Senses Using Topic Models
Jey Han Lau
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Paul Cook
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Diana McCarthy
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Spandana Gella
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Timothy Baldwin
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LexSemTm: A Semantic Dataset Based on All-words Unsupervised Sense Distribution Learning
Andrew Bennett
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Timothy Baldwin
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Jey Han Lau
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Diana McCarthy
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Francis Bond
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A Sense-Topic Model for Word Sense Induction with Unsupervised Data Enrichment
Jing Wang
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Mohit Bansal
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Kevin Gimpel
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Brian D. Ziebart
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Clement T. Yu
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No URLs Found
Field Of Study
Task
Semantic Similarity
Information Retrieval
Approach
Generative Model
Language
English
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