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» Learning to rank for information retrieval (LR4IR 2008)
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SIGIR
2008
ACM
14 years 11 months ago
Enhancing web search by promoting multiple search engine use
Any given Web search engine may provide higher quality results than others for certain queries. Therefore, it is in users' best interest to utilize multiple search engines. I...
Ryen W. White, Matthew Richardson, Mikhail Bilenko...
CN
2006
163views more  CN 2006»
14 years 11 months ago
A framework for mining evolving trends in Web data streams using dynamic learning and retrospective validation
The expanding and dynamic nature of the Web poses enormous challenges to most data mining techniques that try to extract patterns from Web data, such as Web usage and Web content....
Olfa Nasraoui, Carlos Rojas, Cesar Cardona
TREC
2004
15 years 1 months ago
Amberfish at the TREC 2004 Terabyte Track
The TREC 2004 Terabyte Track evaluated information retrieval in largescale text collections, using a set of 25 million documents (426 GB). This paper gives an overview of our expe...
Nassib Nassar
JCIT
2008
93views more  JCIT 2008»
14 years 11 months ago
A search quality evaluation based on objective-subjective method
Commercial search engines, especially meta-search engines was designed to retrieve the information by submitting users' queries to multiple conventional search engines and in...
Fugui Wang, Yajun Du, Qinhua Dong
ICDE
2008
IEEE
203views Database» more  ICDE 2008»
16 years 1 months ago
Training Linear Discriminant Analysis in Linear Time
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. It has been widely used in many fields of information proces...
Deng Cai, Xiaofei He, Jiawei Han