Paper Info
Title
EL Description Logic Modeling Querying Web and Learning Imperfect User Preferences
Abstract
In this position paper we share ideas on modeling querying web resources by (imperfect) combination of particular user preferences based on description logic. Our basic assumption is, that web resources are modeled crisp. Imperfection (uncertainty, vagueness,...) comes from user context and preferences. We oer a model based on connection be- tween three EL-description logic systems: classical, annotated(fuzzy) and a new variant of Bayesian description logic. The Bayesian part enables learning each single user's combination function and concepts. In (2) R. Fagin et al. propose heuristics for a middleware for finding best (top-k) answer when the data that we wish to access and combine may reside in a variety of web repositories. We can look to the Fagin's model as working with fuzzy RDF data (ordered by user preference of particular attribute) and using a combination function providing global score for ordering of resources. Our main
Year
Venue
Keywords
2006
URSW
description logic,middleware
Field
DocType
Citations 
Web resource,Vagueness,Imperfect,Information retrieval,Computer science,Position paper,Fuzzy logic,Description logic,Theoretical computer science,Bayesian probability
Conference
0
PageRank 
References 
Authors
0.34
4
1
Name
Order
Citations
PageRank
Peter Vojtás133633.41