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» Learning consumer preferences using semantic similarity
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EMNLP
2007
13 years 11 months ago
LEDIR: An Unsupervised Algorithm for Learning Directionality of Inference Rules
Semantic inference is a core component of many natural language applications. In response, several researchers have developed algorithms for automatically learning inference rules...
Rahul Bhagat, Patrick Pantel, Eduard H. Hovy
EWCBR
2000
Springer
14 years 1 months ago
A Case-Based Reasoning Approach to Collaborative Filtering
Collaborative filtering systems make recommendations based on the accumulation of ratings by many users. The process has a case-based reasoning flavor: recommendations are generate...
Robin D. Burke
ACL
2008
13 years 11 months ago
Sentence Simplification for Semantic Role Labeling
Parse-tree paths are commonly used to incorporate information from syntactic parses into NLP systems. These systems typically treat the paths as atomic (or nearly atomic) features...
David Vickrey, Daphne Koller
BIRD
2007
Springer
14 years 1 months ago
An Evaluation of Text Retrieval Methods for Similarity Search of Multi-dimensional NMR-Spectra
Abstract. Searching and mining nuclear magnetic resonance (NMR)spectra of naturally occurring substances is an important task to investigate new potentially useful chemical compoun...
Alexander Hinneburg, Andrea Porzel, Karina Wolfram
CORR
2002
Springer
132views Education» more  CORR 2002»
13 years 9 months ago
Exploiting Synergy Between Ontologies and Recommender Systems
Recommender systems learn about user preferences over time, automatically finding things of similar interest. This reduces the burden of creating explicit queries. Recommender sys...
Stuart E. Middleton, Harith Alani, David De Roure