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» Using Temporal Data for Making Recommendations
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STOC
2004
ACM
145views Algorithms» more  STOC 2004»
15 years 9 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
ICMI
2000
Springer
138views Biometrics» more  ICMI 2000»
15 years 1 months ago
Multimodal Speaker Detection Using Input/Output Dynamic Bayesian Networks
Inferring users' actions and intentions forms an integral part of design and development of any human-computer interface. The presence of noisy and at times ambiguous sensory ...
Vladimir Pavlovic, Ashutosh Garg, James M. Rehg
ISSA
2004
14 years 11 months ago
Categorizing Vulnerabilities Using Data Clustering Techniques
Vulnerability scanning is one of the proactive information security technologies in the Internet and network security domain. However, the current vulnerability scanner (VS) produ...
Yun (Lillian) Li
ML
2002
ACM
154views Machine Learning» more  ML 2002»
14 years 9 months ago
Technical Update: Least-Squares Temporal Difference Learning
TD() is a popular family of algorithms for approximate policy evaluation in large MDPs. TD() works by incrementally updating the value function after each observed transition. It h...
Justin A. Boyan
MOBISYS
2011
ACM
14 years 10 days ago
AppJoy: personalized mobile application discovery
The explosive growth of the mobile application market has made it a significant challenge for the users to find interesting applications in crowded App Stores. To alleviate this...
Bo Yan, Guanling Chen