DocumentCode
1443211
Title
Semantic Web Support for Intelligent Search and Retrieval of Business Knowledge
Author
Tamma, Valentina
Author_Institution
Univ. of Liverpool, Liverpool, UK
Volume
25
Issue
1
fYear
2010
Firstpage
84
Lastpage
88
Abstract
In this article we present our experience developing QuestSemantics (QS), an agent-based platform that uses fine-grained business knowledge to support semiautomatic discovery, annotation, filtering and retrieval of information resources on the Internet and in intranets. We designed QS to maximize the separation between the different types of knowledge represented-domain versus task-specific knowledge, and application versus generic knowledge. The goal of this separation is to achieve reusability and easy customization of the platform´s various agents, thus allowing semantics based search in various task and domain scenarios.
Keywords
Internet; business data processing; data mining; information filtering; knowledge representation; semantic Web; software agents; Internet; QuestSemantics; agent-based platform; business knowledge; fine-grained business knowledge; information filtering; information resource retrieval; intelligent retrieval; intelligent search; intranets; knowledge representation; semantic Web; semantic based search; semiautomatic discovery; task-specific knowledge; Information filtering; Information filters; Information resources; Information retrieval; Internet; Semantic Web; Agents; Semantic Web; information retrieval; ontologies;
fLanguage
English
Journal_Title
Intelligent Systems, IEEE
Publisher
ieee
ISSN
1541-1672
Type
jour
DOI
10.1109/MIS.2010.25
Filename
5432263
Link To Document