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» Parallel learning to rank for information retrieval
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DOCENG
2006
ACM
14 years 1 months ago
NEWPAR: an automatic feature selection and weighting schema for category ranking
Category ranking provides a way to classify plain text documents into a pre-determined set of categories. This work proposes to have a look at typical document collections and ana...
Fernando Ruiz-Rico, José Luis Vicedo Gonz&a...
CIKM
2009
Springer
14 years 2 months ago
Enabling multi-level relevance feedback on pubmed by integrating rank learning into DBMS
Background: Finding relevant articles from PubMed is challenging because it is hard to express the user’s specific intention in the given query interface, and a keyword query ty...
Hwanjo Yu, Taehoon Kim, Jinoh Oh, Ilhwan Ko, Sungc...
SIGIR
2004
ACM
14 years 1 months ago
Learning to cluster web search results
Organizing Web search results into clusters facilitates users' quick browsing through search results. Traditional clustering techniques are inadequate since they don't g...
Hua-Jun Zeng, Qi-Cai He, Zheng Chen, Wei-Ying Ma, ...
SAC
2008
ACM
13 years 7 months ago
Pattern ranking for semi-automatic ontology construction
When developing semantic applications, the construction of ontologies is a crucial part. We are developing a semiautomatic ontology construction approach, OntoCase, relying on ont...
Eva Blomqvist
CIKM
2001
Springer
14 years 6 days ago
PowerDB-IR - Information Retrieval on Top of a Database Cluster
Our current concern is a scalable infrastructure for information retrieval (IR) with up-to-date retrieval results in the presence of frequent, continuous updates. Timely processin...
Torsten Grabs, Klemens Böhm, Hans-Jörg S...