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RIAO
2000
13 years 8 months ago
Allowing users to weight search terms
Informationretrieval systems typically weight the importance of search terms according to document and collection statistics (such as by using tf idf scores, where less commonterm...
Ronald Fagin, Yoëlle S. Maarek
WWW
2007
ACM
14 years 8 months ago
Modeling user behavior in recommender systems based on maximum entropy
We propose a model for user purchase behavior in online stores that provide recommendation services. We model the purchase probability given recommendations for each user based on...
Tomoharu Iwata, Kazumi Saito, Takeshi Yamada
MIR
2005
ACM
140views Multimedia» more  MIR 2005»
14 years 1 months ago
Multiple random walk and its application in content-based image retrieval
In this paper, we propose a transductive learning method for content-based image retrieval: Multiple Random Walk (MRW). Its basic idea is to construct two generative models by mea...
Jingrui He, Hanghang Tong, Mingjing Li, Wei-Ying M...
RECSYS
2010
ACM
13 years 7 months ago
Interactive recommendations in social endorsement networks
An increasing number of social networking platforms are giving users the option to endorse entities that they find appealing, such as videos, photos, or even other users. We defin...
Theodoros Lappas, Dimitrios Gunopulos
ECIR
2003
Springer
13 years 9 months ago
A Hybrid Relevance-Feedback Approach to Text Retrieval
Abstract. Relevance feedback (RF) has been an effective query modification approach to improving the performance of information retrieval (IR) by interactively asking a user whet...
Zhao Xu, Xiaowei Xu, Kai Yu, Volker Tresp