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SIGIR
2009
ACM
13 years 11 months ago
Risky business: modeling and exploiting uncertainty in information retrieval
Most retrieval models estimate the relevance of each document to a query and rank the documents accordingly. However, such an approach ignores the uncertainty associated with the ...
Jianhan Zhu, Jun Wang, Ingemar J. Cox, Michael J. ...
DELOS
2001
13 years 6 months ago
Relevance Feedback for Best Match Term Weighting Algorithms in Information Retrieval
Personalisation in full text retrieval or full text filtering implies reweighting of the query terms based on some explicit or implicit feedback from the user. Relevance feedback i...
Djoerd Hiemstra, Stephen E. Robertson
SIGIR
2003
ACM
13 years 10 months ago
Bayesian extension to the language model for ad hoc information retrieval
We propose a Bayesian extension to the ad-hoc Language Model. Many smoothed estimators used for the multinomial query model in ad-hoc Language Models (including Laplace and Bayes-...
Hugo Zaragoza, Djoerd Hiemstra, Michael E. Tipping
SIGIR
2010
ACM
13 years 9 months ago
Estimation of statistical translation models based on mutual information for ad hoc information retrieval
As a principled approach to capturing semantic relations of words in information retrieval, statistical translation models have been shown to outperform simple document language m...
Maryam Karimzadehgan, ChengXiang Zhai
RIAO
2000
13 years 6 months ago
Allowing users to weight search terms
Informationretrieval systems typically weight the importance of search terms according to document and collection statistics (such as by using tf idf scores, where less commonterm...
Ronald Fagin, Yoëlle S. Maarek