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WWW
2008
ACM
14 years 10 months ago
Learning to rank relational objects and its application to web search
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
WWW
2004
ACM
14 years 10 months ago
Web-scale information extraction in knowitall: (preliminary results)
Manually querying search engines in order to accumulate a large body of factual information is a tedious, error-prone process of piecemeal search. Search engines retrieve and rank...
Oren Etzioni, Michael J. Cafarella, Doug Downey, S...
KDD
2005
ACM
194views Data Mining» more  KDD 2005»
14 years 10 months ago
Web object indexing using domain knowledge
Web object is defined to represent any meaningful object embedded in web pages (e.g. images, music) or pointed to by hyperlinks (e.g. downloadable files). Users usually search for...
Muyuan Wang, Zhiwei Li, Lie Lu, Wei-Ying Ma, Naiya...
VLDB
2008
ACM
170views Database» more  VLDB 2008»
14 years 10 months ago
A multi-ranker model for adaptive XML searching
The evolution of computing technology suggests that it has become more feasible to offer access to Web information in a ubiquitous way, through various kinds of interaction device...
Ho Lam Lau, Wilfred Ng
DASFAA
2009
IEEE
191views Database» more  DASFAA 2009»
14 years 4 months ago
Benchmarking Performance-Critical Components in a Native XML Database System
The rapidly increasing number of XML-related applications indicates a growing need for efficient, dynamic, and native XML support in database management systems (XDBMS). So far, bo...
Karsten Schmidt 0002, Sebastian Bächle, Theo ...