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CIKM
2010
Springer
14 years 8 months ago
Term necessity prediction
The probability that a term appears in relevant documents ( ) is a fundamental quantity in several probabilistic retrieval models, however it is difficult to estimate without rele...
Le Zhao, Jamie Callan
SIGIR
2011
ACM
14 years 20 days ago
Social context summarization
We study a novel problem of social context summarization for Web documents. Traditional summarization research has focused on extracting informative sentences from standard docume...
Zi Yang, Keke Cai, Jie Tang, Li Zhang, Zhong Su, J...
SIGIR
2002
ACM
14 years 9 months ago
Finding relevant documents using top ranking sentences: an evaluation of two alternative schemes
In this paper we present an evaluation of techniques that are designed to encourage web searchers to interact more with the results of a web search. Two specific techniques are ex...
Ryen White, Ian Ruthven, Joemon M. Jose
IPM
2008
100views more  IPM 2008»
14 years 10 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
CIKM
2004
Springer
15 years 3 months ago
Stemming and lemmatization in the clustering of finnish text documents
Under construction… Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval – clustering. General Terms Algorithms, Expe...
Tuomo Korenius, Jorma Laurikkala, Kalervo Jär...