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» Learning to rank for information retrieval
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WWW
2010
ACM
16 years 1 months ago
SourceRank: relevance and trust assessment for deep web sources based on inter-source agreement
We consider the problem of deep web source selection and argue that existing source selection methods are inadequate as they are based on local similarity assessment. Specificall...
Raju Balakrishnan, Subbarao Kambhampati
WSDM
2010
ACM
210views Data Mining» more  WSDM 2010»
16 years 3 months ago
Leveraging Temporal Dynamics of Document Content in Relevance Ranking
Many web documents are dynamic, with content changing in varying amounts at varying frequencies. However, current document search algorithms have a static view of the document con...
Jonathan L. Elsas, Susan T. Dumais
DEXA
2010
Springer
230views Database» more  DEXA 2010»
15 years 3 months ago
Hybrid Indexing and Seamless Ranking of Spatial and Textual Features of Web Documents
Abstract. There is a significant commercial and research interest in locationbased web search engines. Given a number of search keywords and one or more locations that a user is in...
Ali Khodaei, Cyrus Shahabi, Chen Li
MM
2009
ACM
203views Multimedia» more  MM 2009»
15 years 11 months ago
Distance metric learning from uncertain side information with application to automated photo tagging
Automated photo tagging is essential to make massive unlabeled photos searchable by text search engines. Conventional image annotation approaches, though working reasonably well o...
Lei Wu, Steven C. H. Hoi, Rong Jin, Jianke Zhu, Ne...
AICCSA
2008
IEEE
245views Hardware» more  AICCSA 2008»
16 years 27 days ago
Rapid and robust ranking of text documents in a dynamically changing corpus
Ranking documents in a selected corpus plays an important role in information retrieval systems. Despite notable advances in this direction, with continuously accumulating text do...
Byung-Hoon Park, Nagiza F. Samatova, Rajesh Munava...