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» The Quantum Probability Ranking Principle for Information Re...
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CIKM
2009
Springer
15 years 6 months ago
Post-rank reordering: resolving preference misalignments between search engines and end users
No search engine is perfect. A typical type of imperfection is the preference misalignment between search engines and end users, e.g., from time to time, web users skip higherrank...
Chao Liu, Mei Li, Yi-Min Wang
IPM
2000
142views more  IPM 2000»
14 years 11 months ago
Adapting a diagnostic problem-solving model to information retrieval
In this paper, a competition-based connectionist model for diagnostic problem-solving is adapted to information retrieval. In this model, we treat documents as \disorders" an...
Inien Syu, Sheau-Dong Lang
CIKM
2008
Springer
15 years 1 months ago
Efficient and effective link analysis with precomputed salsa maps
SALSA is a link-based ranking algorithm that takes the result set of a query as input, extends the set to include additional neighboring documents in the web graph, and performs a...
Marc Najork, Nick Craswell
SIGIR
2012
ACM
13 years 2 months ago
Learning to suggest: a machine learning framework for ranking query suggestions
We consider the task of suggesting related queries to users after they issue their initial query to a web search engine. We propose a machine learning approach to learn the probab...
Umut Ozertem, Olivier Chapelle, Pinar Donmez, Emre...
ECIR
2008
Springer
15 years 1 months ago
Utilizing Passage-Based Language Models for Document Retrieval
Abstract. We show that several previously proposed passage-based document ranking principles, along with some new ones, can be derived from the same probabilistic model. We use lan...
Michael Bendersky, Oren Kurland