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A probabilistic relational approach for web document clustering
- Publication Year :
- 2010
- Publisher :
- Pergamon, 2010.
-
Abstract
- The exponential growth of information available on the World Wide Web, and retrievable by search engines, has implied the necessity to develop efficient and effective methods for organizing relevant contents. In this field document clustering plays an important role and remains an interesting and challenging problem in the field of web computing. In this paper we present a document clustering method, which takes into account both contents information and hyperlink structure of web page collection, where a document is viewed as a set of semantic units. We exploit this representation to determine the strength of a relation between two linked pages and to define a relational clustering algorithm based on a probabilistic graph representation. The experimental results show that the proposed approach, called RED-clustering, outperforms two of the most well known clustering algorithm as k-Means and Expectation Maximization.
- Subjects :
- Information retrieval
Fuzzy clustering
Relational document clustering, Relational web structure estimation
Computer science
Correlation clustering
Constrained clustering
INF/01 - INFORMATICA
Library and Information Sciences
Management Science and Operations Research
Document clustering
computer.software_genre
Computer Science Applications
Data stream clustering
MAT/09 - RICERCA OPERATIVA
Web page
Media Technology
Canopy clustering algorithm
Data mining
Cluster analysis
computer
Information Systems
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....42e75eeabc9acaa1c82b7ae8ff7ae637