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KDD
2006
ACM
145views Data Mining» more  KDD 2006»
14 years 9 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
14 years 9 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
KDD
2005
ACM
143views Data Mining» more  KDD 2005»
14 years 9 months ago
SVM selective sampling for ranking with application to data retrieval
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...
Hwanjo Yu
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 9 months ago
Probabilistic author-topic models for information discovery
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
KDD
2003
ACM
205views Data Mining» more  KDD 2003»
14 years 9 months ago
The data mining approach to automated software testing
In today's industry, the design of software tests is mostly based on the testers' expertise, while test automation tools are limited to execution of pre-planned tests on...
Mark Last, Menahem Friedman, Abraham Kandel
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