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» The Massive User Modelling System (MUMS)
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VISSYM
2004
13 years 6 months ago
Visualization For Public-Resource Climate Modeling
Climateprediction.net aims to harness the spare CPU cycles of a million individual users' PCs to run a massive ensemble of climate simulations using an up-to-date, full-scale...
J. P. R. B. Walton, D. Frame, D. A. Stainforth
KES
2007
Springer
13 years 5 months ago
KeyGraph-based chance discovery for mobile contents management system
Chance discovery provides a way to find rare but very important events for future decision making. It can be applied to stock market prediction, earthquake alarm, intrusion detect...
Kyung-Joong Kim, Myung-Chul Jung, Sung-Bae Cho
AUSDM
2007
Springer
107views Data Mining» more  AUSDM 2007»
13 years 11 months ago
Preference Networks: Probabilistic Models for Recommendation Systems
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh
ICDM
2009
IEEE
148views Data Mining» more  ICDM 2009»
13 years 12 months ago
Hierarchical Bayesian Models for Collaborative Tagging Systems
—Collaborative tagging systems with user generated content have become a fundamental element of websites such as Delicious, Flickr or CiteULike. By sharing common knowledge, mass...
Markus Bundschus, Shipeng Yu, Volker Tresp, Achim ...
CIKM
2010
Springer
13 years 3 months ago
You are where you tweet: a content-based approach to geo-locating twitter users
We propose and evaluate a probabilistic framework for estimating a Twitter user’s city-level location based purely on the content of the user’s tweets, even in the absence of ...
Zhiyuan Cheng, James Caverlee, Kyumin Lee