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» Learning consumer preferences using semantic similarity
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NAACL
2010
13 years 7 months ago
Learning Dense Models of Query Similarity from User Click Logs
The goal of this work is to integrate query similarity metrics as features into a dense model that can be trained on large amounts of query log data, in order to rank query rewrit...
Fabio De Bona, Stefan Riezler, Keith Hall, Massimi...
AMEC
2003
Springer
14 years 2 months ago
Improving Learning Performance by Applying Economic Knowledge
Digital information economies require information goods producers to learn how to position themselves within a potentially vast product space. Further, the topography of this spac...
Christopher H. Brooks, Robert S. Gazzale, Jeffrey ...
SIGECOM
2003
ACM
122views ECommerce» more  SIGECOM 2003»
14 years 2 months ago
On polynomial-time preference elicitation with value queries
Preference elicitation — the process of asking queries to determine parties’ preferences — is a key part of many problems in electronic commerce. For example, a shopping age...
Martin Zinkevich, Avrim Blum, Tuomas Sandholm
BPM
2006
Springer
115views Business» more  BPM 2006»
14 years 1 months ago
Modeling, Matching and Ranking Services Based on Constraint Hardness
A framework for modeling Semantic Web Service is proposed. It is based on Description Logic (DL), hence it is endowed with a formal semantics and, in addition, it allows for expres...
Claudia d'Amato, Steffen Staab
DICTA
2003
13 years 11 months ago
Learning Semantic Concepts from Visual Data Using Neural Networks
For content-based image retrieval techniques, query image is used to pick up and rank some relevant images from a database using some certain similarity metric. If semantic feature...
Xiaohang Ma, Dianhui Wang