Title :
Semantic Web Support for Intelligent Search and Retrieval of Business Knowledge
Author :
Tamma, Valentina
Author_Institution :
Univ. of Liverpool, Liverpool, UK
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;
Journal_Title :
Intelligent Systems, IEEE
DOI :
10.1109/MIS.2010.25