Sciweavers

76 search results - page 1 / 16
» Are click-through data adequate for learning web search rank...
Sort
View
WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
14 years 2 months ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
CIKM
2008
Springer
13 years 6 months ago
Are click-through data adequate for learning web search rankings?
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Zhicheng Dou, Ruihua Song, Xiaojie Yuan, Ji-Rong W...
WEBDB
2010
Springer
155views Database» more  WEBDB 2010»
13 years 10 months ago
Learning Topical Transition Probabilities in Click Through Data with Regression Models
The transition of search engine users’ intents has been studied for a long time. The knowledge of intent transition, once discovered, can yield a better understanding of how diď...
Xiao Zhang, Prasenjit Mitra
ICDE
2009
IEEE
251views Database» more  ICDE 2009»
14 years 6 months ago
Contextual Ranking of Keywords Using Click Data
The problem of automatically extracting the most interesting and relevant keyword phrases in a document has been studied extensively as it is crucial for a number of applications. ...
Utku Irmak, Vadim von Brzeski, Reiner Kraft
SIGIR
2011
ACM
12 years 7 months ago
Pseudo test collections for learning web search ranking functions
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...