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WEBI
2005
Springer
14 years 26 days ago
A Semi-Supervised Document Clustering Algorithm Based on EM
Document clustering is a very hard task in Automatic Text Processing since it requires to extract regular patterns from a document collection without a priori knowledge on the cat...
Leonardo Rigutini, Marco Maggini
LREC
2008
174views Education» more  LREC 2008»
13 years 8 months ago
UnsuParse: unsupervised Parsing with unsupervised Part of Speech Tagging
Based on simple methods such as observing word and part of speech tag co-occurrence and clustering, we generate syntactic parses of sentences in an entirely unsupervised and self-...
Christian Hänig, Stefan Bordag, Uwe Quasthoff
APIN
2007
118views more  APIN 2007»
13 years 7 months ago
Using genetic algorithms to reorganize superpeer structure in peer to peer networks
In this thesis, we describe a genetic algorithm for optimizing the superpeer structure of semantic peer to peer networks. Peer to peer, also called P2P, networks enable us to sear...
Jaymin Kessler, Khaled Rasheed, Ismailcem Budak Ar...
SSDBM
2005
IEEE
218views Database» more  SSDBM 2005»
14 years 29 days ago
The "Best K" for Entropy-based Categorical Data Clustering
With the growing demand on cluster analysis for categorical data, a handful of categorical clustering algorithms have been developed. Surprisingly, to our knowledge, none has sati...
Keke Chen, Ling Liu
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
14 years 7 months ago
A framework for ontology-driven subspace clustering
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
Jinze Liu, Wei Wang 0010, Jiong Yang