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» Using Temporal Data for Making Recommendations
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IJCAI
2007
14 years 11 months ago
ItemRank: A Random-Walk Based Scoring Algorithm for Recommender Engines
Recommender systems are an emerging technology that helps consumers to find interesting products. A recommender system makes personalized product suggestions by extracting knowle...
Marco Gori, Augusto Pucci
SIGIR
2009
ACM
15 years 3 months ago
Personalized tag recommendation using graph-based ranking on multi-type interrelated objects
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...
Ziyu Guan, Jiajun Bu, Qiaozhu Mei, Chun Chen, Can ...
GFKL
2005
Springer
114views Data Mining» more  GFKL 2005»
15 years 3 months ago
Attribute-aware Collaborative Filtering
One of the key challenges in large information systems such as online shops and digital libraries is to discover the relevant knowledge from the enormous volume of information. Rec...
Karen H. L. Tso, Lars Schmidt-Thieme
CIKM
2004
Springer
15 years 2 months ago
Framework and algorithms for trend analysis in massive temporal data sets
Mining massive temporal data streams for significant trends, emerging buzz, and unusually high or low activity is an important problem with several commercial applications. In th...
Sreenivas Gollapudi, D. Sivakumar
AAAI
2010
14 years 11 months ago
Collaborative Filtering Meets Mobile Recommendation: A User-Centered Approach
With the increasing popularity of location tracking services such as GPS, more and more mobile data are being accumulated. Based on such data, a potentially useful service is to m...
Vincent Wenchen Zheng, Bin Cao, Yu Zheng, Xing Xie...