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ICDM
2008
IEEE
150views Data Mining» more  ICDM 2008»
15 years 4 months ago
Pseudolikelihood EM for Within-network Relational Learning
In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
Rongjing Xiang, Jennifer Neville
78
Voted
IADIS
2004
14 years 11 months ago
Recognizing Article Errors Based on the Three Head Words
In this paper, we present a statistical model for detecting article errors, which Japanese learners of English often make in English writing. The model detects article errors base...
Ryo Nagata, Fumito Masui, Atsuo Kawai, Naoki Isu
84
Voted
KDD
2007
ACM
136views Data Mining» more  KDD 2007»
15 years 10 months ago
Information genealogy: uncovering the flow of ideas in non-hyperlinked document databases
We now have incrementally-grown databases of text documents ranging back for over a decade in areas ranging from personal email, to news-articles and conference proceedings. While...
Benyah Shaparenko, Thorsten Joachims
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
15 years 10 months ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
116
Voted
KDD
2003
ACM
191views Data Mining» more  KDD 2003»
15 years 10 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle