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AAAI
2010
13 years 8 months ago
A Two-Dimensional Topic-Aspect Model for Discovering Multi-Faceted Topics
This paper presents the Topic-Aspect Model (TAM), a Bayesian mixture model which jointly discovers topics and aspects. We broadly define an aspect of a document as a characteristi...
Michael Paul, Roxana Girju
ACL
2008
13 years 8 months ago
An Unsupervised Vector Approach to Biomedical Term Disambiguation: Integrating UMLS and Medline
This paper introduces an unsupervised vector approach to disambiguate words in biomedical text that can be applied to all-word disambiguation. We explore using contextual informat...
Bridget McInnes
KDD
2008
ACM
257views Data Mining» more  KDD 2008»
14 years 7 months ago
Knowledge discovery of semantic relationships between words using nonparametric bayesian graph model
We developed a model based on nonparametric Bayesian modeling for automatic discovery of semantic relationships between words taken from a corpus. It is aimed at discovering seman...
Issei Sato, Minoru Yoshida, Hiroshi Nakagawa
ACL
2011
12 years 11 months ago
Discovering Sociolinguistic Associations with Structured Sparsity
We present a method to discover robust and interpretable sociolinguistic associations from raw geotagged text data. Using aggregate demographic statistics about the authors’ geo...
Jacob Eisenstein, Noah A. Smith, Eric P. Xing
RIAO
2000
13 years 8 months ago
Discovering and Comparing Topic Hierarchies
Hierarchies have been used for organization, summarization, and access to information, yet a lingering issue is how best to construct them. In this paper, our goal is to automatic...
Dawn Lawrie, W. Bruce Croft