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» Query Expansion and Query Reduction in Document Retrieval
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SIGIR
2008
ACM
13 years 10 months ago
Learning to rank at query-time using association rules
Some applications have to present their results in the form of ranked lists. This is the case of many information retrieval applications, in which documents must be sorted accordi...
Adriano Veloso, Humberto Mossri de Almeida, Marcos...
PVLDB
2008
205views more  PVLDB 2008»
13 years 9 months ago
Making SENSE: socially enhanced search and exploration
Online communities like Flickr, del.icio.us and YouTube have established themselves as very popular and powerful services for publishing and searching contents, but also for ident...
Tom Crecelius, Mouna Kacimi, Sebastian Michel, Tho...
DASFAA
2010
IEEE
252views Database» more  DASFAA 2010»
14 years 2 months ago
Effectively Inferring the Search-for Node Type in XML Keyword Search
xml keyword search provides a simple and user-friendly way of retrieving data from xml databases, but the ambiguities of keywords make it difficult to effectively answer keyword qu...
Jiang Li, Junhu Wang
JCDL
2010
ACM
187views Education» more  JCDL 2010»
14 years 4 days ago
Social network document ranking
In search engines, ranking algorithms measure the importance and relevance of documents mainly based on the contents and relationships between documents. User attributes are usual...
Liang Gou, Xiaolong Zhang, Hung-Hsuan Chen, Jung-H...
HICSS
2006
IEEE
163views Biometrics» more  HICSS 2006»
14 years 4 months ago
Learning Ranking vs. Modeling Relevance
The classical (ad hoc) document retrieval problem has been traditionally approached through ranking according to heuristically developed functions (such as tf.idf or bm25) or gene...
Dmitri Roussinov, Weiguo Fan