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TRECVID
2008
13 years 9 months ago
XJTU at TRECVID2008 High-Level Feature Extraction
In this paper, we present our experiments in TRECVID 2008 about High-Level feature extraction task. This is the first year for our participation in TRECVID, our system adopts some...
Zhe Wang, Guizhong Liu, Xueming Qian, Zhi Li, Danp...
STOC
2004
ACM
145views Algorithms» more  STOC 2004»
14 years 8 months ago
Using mixture models for collaborative filtering
A collaborative filtering system at an e-commerce site or similar service uses data about aggregate user behavior to make recommendations tailored to specific user interests. We d...
Jon M. Kleinberg, Mark Sandler
SP
2002
IEEE
141views Security Privacy» more  SP 2002»
13 years 7 months ago
Collaborative Filtering with Privacy
Server-based collaborative filtering systems have been very successful in e-commerce and in direct recommendation applications. In future, they have many potential applications in...
John F. Canny
COMAD
2009
13 years 8 months ago
Trust-Based Infinitesimals for Enhanced Collaborative Filtering
In this paper we propose a novel recommender system which enhances user-based collaborative filtering by using a trust-based social network. Our main idea is to use infinitesimal ...
Maria Chowdhury, Alex Thomo, William W. Wadge
KI
2010
Springer
13 years 6 months ago
An Extensible Modular Recognition Concept That Makes Activity Recognition Practical
Abstract. In mobile and ubiquitous computing, there is a strong need for supporting different users with different interests, needs, and demands. Activity recognition systems for c...
Martin Berchtold, Matthias Budde, Hedda Rahel Schm...