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KDD
2009
ACM
173views Data Mining» more  KDD 2009»
16 years 7 months ago
Constant-factor approximation algorithms for identifying dynamic communities
We propose two approximation algorithms for identifying communities in dynamic social networks. Communities are intuitively characterized as "unusually densely knit" sub...
Chayant Tantipathananandh, Tanya Y. Berger-Wolf
KDD
2009
ACM
223views Data Mining» more  KDD 2009»
16 years 7 months ago
Collaborative filtering with temporal dynamics
Customer preferences for products are drifting over time. Product perception and popularity are constantly changing as new selection emerges. Similarly, customer inclinations are ...
Yehuda Koren
KDD
2009
ACM
262views Data Mining» more  KDD 2009»
16 years 7 months ago
Sentiment analysis of blogs by combining lexical knowledge with text classification
The explosion of user-generated content on the Web has led to new opportunities and significant challenges for companies, that are increasingly concerned about monitoring the disc...
Prem Melville, Wojciech Gryc, Richard D. Lawrence
KDD
2009
ACM
167views Data Mining» more  KDD 2009»
16 years 7 months ago
Seven pitfalls to avoid when running controlled experiments on the web
Controlled experiments, also called randomized experiments and A/B tests, have had a profound influence on multiple fields, including medicine, agriculture, manufacturing, and adv...
Thomas Crook, Brian Frasca, Ron Kohavi, Roger Long...
KDD
2009
ACM
140views Data Mining» more  KDD 2009»
16 years 7 months ago
Improving clustering stability with combinatorial MRFs
: ? Improving Clustering Stability with Combinatorial MRFs Bekkerman, Ron; Scholz, Martin; Viswanathan, Krishnamurthy HP Laboratories HPL-2009-46 Clustering stability, combinatoria...
Ron Bekkerman, Martin Scholz, Krishnamurthy Viswan...
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