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KDD
2008
ACM
138views Data Mining» more  KDD 2008»
16 years 7 months ago
A visual-analytic toolkit for dynamic interaction graphs
In this article we describe a visual-analytic tool for the interrogation of evolving interaction network data such as those found in social, bibliometric, WWW and biological appli...
Xintian Yang, Sitaram Asur, Srinivasan Parthasarat...
KDD
2008
ACM
159views Data Mining» more  KDD 2008»
16 years 7 months ago
Semi-supervised learning with data calibration for long-term time series forecasting
Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
Haibin Cheng, Pang-Ning Tan
KDD
2008
ACM
146views Data Mining» more  KDD 2008»
16 years 7 months ago
Spotting out emerging artists using geo-aware analysis of P2P query strings
Record label companies would like to identify potential artists as early as possible in their careers, before other companies approach the artists with competing contracts. The va...
Noam Koenigstein, Yuval Shavitt, Tomer Tankel
KDD
2007
ACM
160views Data Mining» more  KDD 2007»
16 years 7 months ago
Show me the money!: deriving the pricing power of product features by mining consumer reviews
The increasing pervasiveness of the Internet has dramatically changed the way that consumers shop for goods. Consumergenerated product reviews have become a valuable source of inf...
Nikolay Archak, Anindya Ghose, Panagiotis G. Ipeir...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 7 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
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