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» Ranking Approaches for Microblog Search
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ALENEX
2009
172views Algorithms» more  ALENEX 2009»
14 years 8 months ago
Rank Aggregation: Together We're Strong
We consider the problem of finding a ranking of a set of elements that is "closest to" a given set of input rankings of the elements; more precisely, we want to find a p...
Frans Schalekamp, Anke van Zuylen
ICDCS
2010
IEEE
14 years 8 months ago
Secure Ranked Keyword Search over Encrypted Cloud Data
As Cloud Computing becomes prevalent, sensitive information are being increasingly centralized into the cloud. For the protection of data privacy, sensitive data has to be encrypte...
Cong Wang, Ning Cao, Jin Li, Kui Ren, Wenjing Lou
RECSYS
2010
ACM
14 years 10 months ago
Nantonac collaborative filtering: a model-based approach
A recommender system has to collect users' preference data. To collect such data, rating or scoring methods that use rating scales, such as good-fair-poor or a five-point-sca...
Toshihiro Kamishima, Shotaro Akaho
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
13 years 6 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
ICDE
2009
IEEE
170views Database» more  ICDE 2009»
16 years 11 days ago
Semantics of Ranking Queries for Probabilistic Data and Expected Ranks
Abstract-- When dealing with massive quantities of data, topk queries are a powerful technique for returning only the k most relevant tuples for inspection, based on a scoring func...
Graham Cormode, Feifei Li, Ke Yi