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» Using Information Extraction to Improve Document Retrieval
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SIGIR
2012
ACM
13 years 9 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
CIKM
2010
Springer
15 years 4 months ago
Wisdom of the ages: toward delivering the children's web with the link-based agerank algorithm
Though children frequently use web search engines to learn, interact, and be entertained, modern web search engines are poorly suited to children's needs, requiring relativel...
Karl Gyllstrom, Marie-Francine Moens
SIGIR
2008
ACM
15 years 6 months ago
Automatically identifying localizable queries
Personalization of web search results as a technique for improving user satisfaction has received notable attention in the research community over the past decade. Much of this wo...
Michael J. Welch, Junghoo Cho
WSDM
2009
ACM
125views Data Mining» more  WSDM 2009»
16 years 1 months ago
Less is more: sampling the neighborhood graph makes SALSA better and faster
In this paper, we attempt to improve the effectiveness and the efficiency of query-dependent link-based ranking algorithms such as HITS, MAX and SALSA. All these ranking algorith...
Marc Najork, Sreenivas Gollapudi, Rina Panigrahy
CIKM
2009
Springer
16 years 1 months ago
Enabling multi-level relevance feedback on pubmed by integrating rank learning into DBMS
Background: Finding relevant articles from PubMed is challenging because it is hard to express the user’s specific intention in the given query interface, and a keyword query ty...
Hwanjo Yu, Taehoon Kim, Jinoh Oh, Ilhwan Ko, Sungc...