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CIKM
2009
Springer
15 years 6 months ago
Learning to rank from Bayesian decision inference
Ranking is a key problem in many information retrieval (IR) applications, such as document retrieval and collaborative filtering. In this paper, we address the issue of learning ...
Jen-Wei Kuo, Pu-Jen Cheng, Hsin-Min Wang
ICDM
2009
IEEE
134views Data Mining» more  ICDM 2009»
14 years 9 months ago
Efficient Discovery of Confounders in Large Data Sets
Given a large transaction database, association analysis is concerned with efficiently finding strongly related objects. Unlike traditional associate analysis, where relationships ...
Wenjun Zhou, Hui Xiong
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
16 years 19 hour ago
Finding tribes: identifying close-knit individuals from employment patterns
We present a family of algorithms to uncover tribes--groups of individuals who share unusual sequences of affiliations. While much work inferring community structure describes lar...
Lisa Friedland, David Jensen
89
Voted
IDEAS
2009
IEEE
104views Database» more  IDEAS 2009»
15 years 6 months ago
An organizational file permission management system using the cellular data system
In designing dynamic situations such as cyberworlds, we the Incrementally Modular Abstraction Hierarchy (IMAH) to be an appropriate mathematical background to model dynamically ch...
Toshio Kodama, Tosiyasu L. Kunii, Yoichi Seki
HICSS
1999
IEEE
125views Biometrics» more  HICSS 1999»
15 years 3 months ago
ASHRAM: Active Summarization and Markup
Typically, searching for information in a document collection amounts to refining a query and then scanning a large number of documents to determine their relevance. Active Summar...
Mary S. Neff, James W. Cooper