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» Learning to rank for information retrieval
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ICTIR
2009
Springer
16 years 26 days ago
Ranking List Dispersion as a Query Performance Predictor
Abstract. In this paper we introduce a novel approach for query performance prediction based on ranking list scores dispersion. Starting from the hypothesis that different score d...
Joaquín Pérez-Iglesias, Lourdes Arau...
JCDL
2010
ACM
187views Education» more  JCDL 2010»
15 years 8 months 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...
WWW
2002
ACM
16 years 7 months ago
Topic-sensitive PageRank
In the original PageRank algorithm for improving the ranking of search-query results, a single PageRank vector is computed, using the link structure of the Web, to capture the rel...
Taher H. Haveliwala
ICDE
2007
IEEE
113views Database» more  ICDE 2007»
16 years 19 days ago
Ranking Query Results using Context-Aware Preferences
To better serve users’ information needs without requiring comprehensive queries from users, a simple yet effective technique is to explore the preferences of users. Since these...
Arthur H. van Bunningen, Maarten M. Fokkinga, Pete...
WWW
2007
ACM
16 years 7 months ago
Web object retrieval
The primary function of current Web search engines is essentially relevance ranking at the document level. However, myriad structured information about real-world objects is embed...
Zaiqing Nie, Yunxiao Ma, Shuming Shi, Ji-Rong Wen,...