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CIKM
2010
Springer
13 years 6 months ago
Online learning for recency search ranking using real-time user feedback
Traditional machine-learned ranking algorithms for web search are trained in batch mode, which assume static relevance of documents for a given query. Although such a batch-learni...
Taesup Moon, Lihong Li, Wei Chu, Ciya Liao, Zhaohu...
NLDB
2007
Springer
14 years 1 months ago
Combining Vector Space Model and Multi Word Term Extraction for Semantic Query Expansion
Abstract. In this paper, we target document ranking in a highly technical field with the aim to approximate a ranking that is obtained through an existing ontology (knowledge stru...
Eric SanJuan, Fidelia Ibekwe-Sanjuan, Juan Manuel ...
ICDE
2009
IEEE
170views Database» more  ICDE 2009»
14 years 9 months ago
Semantics of Ranking Queries for Probabilistic Data and Expected Ranks
Abstract-- When dealing with massive quantities of data, topk queries are a powerful technique for returning only the k most relevant tuples for inspection, based on a scoring func...
Graham Cormode, Feifei Li, Ke Yi
DASFAA
2010
IEEE
220views Database» more  DASFAA 2010»
13 years 5 months ago
An Effective Object-Level XML Keyword Search
Keyword search is widely recognized as a convenient way to retrieve information from XML data. In order to precisely meet users' search concerns, we study how to effectively r...
Zhifeng Bao, Jiaheng Lu, Tok Wang Ling, Liang Xu, ...
CIKM
2010
Springer
13 years 6 months ago
Ranking related entities: components and analyses
Related entity finding is the task of returning a ranked list of homepages of relevant entities of a specified type that need to engage in a given relationship with a given sour...
Marc Bron, Krisztian Balog, Maarten de Rijke