Title
An ontology-learning knowledge support system to keep e-organization's knowledge up-to-date: a university case study
Abstract
e-Organizational users can apply semantic engineering solutions to deal with decision-making and task-intensive knowledge requirements supported by Knowledge Management Systems (KMSs). Such optional engineering strategies consider some system types to meet knowledge users' need, aligned with the e-services and e-management qualities required for them. Particularly, in the Knowledge Support System (KSS) field, developers have adopted some Ontology-based technologies to support user's task-knowledge system functionalities. In this paper, an Ontology-Learning Knowledge Support System (OLeKSS) model is proposed as a general component of e-organizations, to keep the ontologies associated with this kind of KMS updated and enriched. Relational Databases (RDBs) are considered complementary knowledge source for Knowledge Acquisition (KA) through a OLeKSS Process (as a subsystem component) based on methodologies for Ontology Learning (OL). In a University case, we had applied a Systemic Methodology for OL (SMOL) from a RDB to update the correspondent host-ontology associated to the University's KSS during this OLeKSS process.
Year
DOI
Venue
2011
10.1007/978-3-642-22961-9_20
EGOVIS
Keywords
Field
DocType
complementary knowledge source,knowledge acquisition,knowledge management systems,olekss process,ontology-learning knowledge support system,university case,university case study,knowledge user,ontology-learning knowledge support,task-intensive knowledge requirement,knowledge support,general component
World Wide Web,Knowledge integration,Domain knowledge,Personal knowledge management,Computer science,Knowledge-based systems,Knowledge management,Knowledge engineering,Knowledge extraction,Knowledge acquisition,Open Knowledge Base Connectivity
Conference
Citations 
PageRank 
References 
2
0.36
30
Authors
2
Name
Order
Citations
PageRank
Richard J. Gil120.36
Maria J. Martín-Bautista220823.79