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KDD
2003
ACM
146views Data Mining» more  KDD 2003»
14 years 9 months ago
Probabilistic discovery of time series motifs
Several important time series data mining problems reduce to the core task of finding approximately repeated subsequences in a longer time series. In an earlier work, we formalize...
Bill Yuan-chi Chiu, Eamonn J. Keogh, Stefano Lonar...
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 9 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
CORR
2004
Springer
218views Education» more  CORR 2004»
13 years 8 months ago
A Dynamic Clustering-Based Markov Model for Web Usage Mining
Markov models have been widely utilized for modelling user web navigation behaviour. In this work we propose a dynamic clustering-based method to increase a Markov model's ac...
José Borges, Mark Levene
EDM
2009
116views Data Mining» more  EDM 2009»
13 years 6 months ago
Dimensions of Difficulty in Translating Natural Language into First-Order Logic
In this paper, we present a study of a large corpus of student logic exercises in which we explore the relationship between two distinct measures of difficulty: the proportion of s...
Dave Barker-Plummer, Richard Cox, Robert Dale
CBMS
2005
IEEE
14 years 2 months ago
An Ontology-Driven Clustering Method for Supporting Gene Expression Analysis
The Gene Ontology (GO) is an important knowledge resource for biologists and bioinformaticians. This paper explores the integration of similarity information derived from GO into ...
Haiying Wang, Francisco Azuaje, Olivier Bodenreide...