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ECIR
2011
Springer
12 years 11 months ago
Learning Models for Ranking Aggregates
Aggregate ranking tasks are those where documents are not the final ranking outcome, but instead an intermediary component. For instance, in expert search, a ranking of candidate ...
Craig Macdonald, Iadh Ounis
JCDL
2006
ACM
143views Education» more  JCDL 2006»
14 years 1 months ago
Categorizing web search results into meaningful and stable categories using fast-feature techniques
When search results against digital libraries and web resources have limited metadata, augmenting them with meaningful and stable category information can enable better overviews ...
Bill Kules, Jack Kustanowitz, Ben Shneiderman
RECSYS
2010
ACM
13 years 7 months ago
Group recommendations with rank aggregation and collaborative filtering
The majority of recommender systems are designed to make recommendations for individual users. However, in some circumstances the items to be selected are not intended for persona...
Linas Baltrunas, Tadas Makcinskas, Francesco Ricci
SIGIR
2009
ACM
14 years 2 months ago
Learning to rank for quantity consensus queries
Web search is increasingly exploiting named entities like persons, places, businesses, addresses and dates. Entity ranking is also of current interest at INEX and TREC. Numerical ...
Somnath Banerjee, Soumen Chakrabarti, Ganesh Ramak...
WWW
2004
ACM
14 years 8 months ago
Random surfer with back step
We present a novel link-based ranking algorithm RBS, which may be viewed as an extension of PageRank by back-step feature. Categories and Subject Descriptors H.3.3 [Information Se...
Marcin Sydow