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» Linguistic Knowledge can Improve Information Retrieval
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CIKM
2005
Springer
16 years 3 days ago
Implicit user modeling for personalized search
Information retrieval systems (e.g., web search engines) are critical for overcoming information overload. A major deficiency of existing retrieval systems is that they generally...
Xuehua Shen, Bin Tan, ChengXiang Zhai
WWW
2010
ACM
15 years 6 months ago
Classification-enhanced ranking
Many have speculated that classifying web pages can improve a search engine's ranking of results. Intuitively results should be more relevant when they match the class of a q...
Paul N. Bennett, Krysta Marie Svore, Susan T. Duma...
ECIR
2003
Springer
15 years 8 months ago
From Uncertain Inference to Probability of Relevance for Advanced IR Applications
Uncertain inference is a probabilistic generalisation of the logical view on databases, ranking documents according to their probabilities that they logically imply the query. For ...
Henrik Nottelmann, Norbert Fuhr
KDD
2010
ACM
252views Data Mining» more  KDD 2010»
15 years 10 months ago
Fast query execution for retrieval models based on path-constrained random walks
Many recommendation and retrieval tasks can be represented as proximity queries on a labeled directed graph, with typed nodes representing documents, terms, and metadata, and labe...
Ni Lao, William W. Cohen
ECIR
2007
Springer
15 years 8 months ago
Automatic Morphological Query Expansion Using Analogy-Based Machine Learning
Information retrieval systems (IRSs) usually suffer from a low ability to recognize a same idea that is expressed in different forms. A way of improving these systems is to take ...
Fabienne Moreau, Vincent Claveau, Pascale Sé...