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» Learning consumer preferences using semantic similarity
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NLE
2010
112views more  NLE 2010»
13 years 8 months ago
A non-negative tensor factorization model for selectional preference induction
Distributional similarity methods have proven to be a valuable tool for the induction of semantic similarity. Up till now, most algorithms use two-way cooccurrence data to compute...
Tim Van de Cruys
CIARP
2004
Springer
14 years 3 months ago
Unsupervised Learning of Ontology-Linked Selectional Preferences
We present a method for extracting selectional preferences of verbs from unannotated text. These selectional preferences are linked to an ontology (e.g. the hypernym relations foun...
Hiram Calvo, Alexander F. Gelbukh
EMNLP
2008
13 years 11 months ago
Learning Graph Walk Based Similarity Measures for Parsed Text
We consider a parsed text corpus as an instance of a labelled directed graph, where nodes represent words and weighted directed edges represent the syntactic relations between the...
Einat Minkov, William W. Cohen
COLING
2002
13 years 9 months ago
Taxonomy Learning - Factoring the Structure of a Taxonomy into a Semantic Classification Decision
The paper examines different possibilities to take advantage of the taxonomic organization of a thesaurus to improve the accuracy of classifying new words into its classes. The re...
Viktor Pekar, Steffen Staab
WEBI
2005
Springer
14 years 3 months ago
Integrating Element and Term Semantics for Similarity-Based XML Document Clustering
Structured link vector model (SLVM) is a recently proposed document representation that takes into account both structural and semantic information for measuring XML document simi...
Jianwu Yang, William K. Cheung, Xiaoou Chen