Paper Info
Title
Knowledge Modelling for Deductive Web Mining
Abstract
Knowledge-intensive methods that can altogether be characterised as deductive web mining (DWM) already act as supporting technology for building the semantic web. Reusable knowledge-level descriptions may further ease the deployment of DWM tools. We developed a multi-dimensional, ontology-based framework, and a collection of problem-solving methods, which enable to characterise DWM applications at an abstract level. We show that the heterogeneity and unboundedness of the web demands for some modifications of the problem-solving method paradigm used in the context of traditional artificial intelligence.
Year
DOI
Venue
2004
10.1007/978-3-540-30202-5_23
Lecture Notes in Computer Science
Keywords
Field
DocType
semantic web,web mining,artificial intelligent
Data mining,Ontology,Knowledge modelling,Web mining,Software deployment,Web intelligence,Computer science,Semantic Web,Knowledge engineering,The Internet
Conference
Volume
ISSN
Citations 
3257
0302-9743
4
PageRank 
References 
Authors
0.72
11
3
Name
Order
Citations
PageRank
Vojtech Svátek128446.24
Martin Labský2236.77
Miroslav Vacura314916.28