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SIGIR
2009
ACM
15 years 6 months ago
2009
ACM
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 ...
104
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SIGIR
2009
ACM
15 years 6 months ago
2009
ACM
With the sheer growth of online user data, it becomes challenging to develop preference learning algorithms that are sufficiently flexible in modeling but also affordable in com...
112
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SIGIR
2009
ACM
15 years 6 months ago
2009
ACM
The selection of indexing terms for representing documents is a key decision that limits how effective subsequent retrieval can be. Often stemming algorithms are used to normaliz...
121
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SIGIR
2009
ACM
15 years 6 months ago
2009
ACM
Social tagging is becoming increasingly popular in many Web 2.0 applications where users can annotate resources (e.g. Web pages) with arbitrary keywords (i.e. tags). A tag recomme...
124
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SIGIR
2009
ACM
15 years 6 months ago
2009
ACM
Recommender Systems, based on collaborative filtering (CF), aim to accurately predict user tastes, by minimising the mean error achieved on hidden test sets of user ratings, afte...