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CIKM
2010
Springer
14 years 10 months ago
Mining topic-level influence in heterogeneous networks
Influence is a complex and subtle force that governs the dynamics of social networks as well as the behaviors of involved users. Understanding influence can benefit various applic...
Lu Liu, Jie Tang, Jiawei Han, Meng Jiang, Shiqiang...
BMCBI
2005
134views more  BMCBI 2005»
14 years 11 months ago
Inherited disorder phenotypes: controlled annotation and statistical analysis for knowledge mining from gene lists
Background: Analysis of inherited diseases and their associated phenotypes is of great importance to gain knowledge of underlying genetic interactions and could ultimately give cl...
Marco Masseroli, Osvaldo Galati, Mauro Manzotti, K...
CIKM
2008
Springer
15 years 1 months ago
Identification of class specific discourse patterns
In this paper we address the problem of extracting important (and unimportant) discourse patterns from call center conversations. Call centers provide dialog based calling-in supp...
Anup Chalamalla, Sumit Negi, L. Venkata Subramania...
KDD
2004
ACM
192views Data Mining» more  KDD 2004»
16 years 8 days ago
Mining and summarizing customer reviews
Merchants selling products on the Web often ask their customers to review the products that they have purchased and the associated services. As e-commerce is becoming more and mor...
Minqing Hu, Bing Liu
SDM
2010
SIAM
283views Data Mining» more  SDM 2010»
15 years 1 months ago
Cascading Spatio-temporal Pattern Discovery: A Summary of Results
Given a collection of Boolean spatio-temporal(ST) event types, the cascading spatio-temporal pattern (CSTP) discovery process finds partially ordered subsets of event-types whose ...
Pradeep Mohan, Shashi Shekhar, James A. Shine, Jam...