Topic-Centric Querying of Web Information Resourcest

Date
2001
Advisor
Instructor
Source Title
Database and Expert Systems Applications
Print ISSN
0302-9743
Electronic ISSN
Publisher
Springer, Berlin, Heidelberg
Volume
2113
Issue
Pages
699 - 711
Language
English
Type
Conference Paper
Journal Title
Journal ISSN
Volume Title
Abstract

This paper deals with the problem of modeling web information resources using expert knowledge and personalized user information, and querying them in terms of topics and topic relationships. We propose a model for web information resources, and a query language SQL-TC (Topic-Centric SQL) to query the model. The model is composed of web-based information resources (XML or HTML documents on the web), expert advice repositories (domain-expert-specified metadata for information resources), and personalized information about users (captured as user profiles, that indicate users’ preferences as to which expert advice they would like to follow, and which to ignore, etc). The query language SQL-TC makes use of the metadata information provided in expert advice repositories and embedded in information resources, and employs user preferences to further refine the query output. Query output objects/tuples are ranked with respect to the (expert-judged and user- preference-revised) importance values of requested topics/metalinks, and the query output is limited by either top n-ranked objects/tuples, or objects/tuples with importance values above a given threshold, or both. © Springer-Verlag Berlin Heidelberg 2001.

Course
Other identifiers
Book Title
Keywords
Computational linguistics, Expert systems, Information science, Metadata, Query languages, Query processing, Expert knowledge, HTML documents, Information resource, Metadata information, Personalized information, User information, Web information, Web-based information, Information use
Citation
Published Version (Please cite this version)