Personal knowledge management for knowledge workers using social semantic technologies. (9th February 2009)

• Record Type: Journal Article
• Authors: Kim, Haklae; Breslin, John G.; Decker, Stefan; Choi, Jaehwa; , Honggee Kim
• Is Part Of: International journal of intelligent information and database systems. Volume 3:Number 1(2009)
• Page Start: 28
• Page End: 43
• Publication Date: 2009-02-09
• Subjects: semantic web -- semantic wiki -- personal knowledge management -- PKM -- folksonomy -- social tagging -- semantics -- knowledge creation -- collaboration -- ontology -- knowledge search -- knowledge retrieval; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

Knowledge workers have different applications and resources in heterogeneous environments for doing their knowledge tasks and they often need to solve a problem through combining several resources. Typical personal knowledge management (PKM) systems do not provide effective ways for representing knowledge worker's unstructured knowledge or idea. In order to provide better knowledge activity for them, we implement Wiki-based social Network Thin client (WANT) that is a wiki-based semantic tagging system for collaborative and communicative knowledge creation and maintenance for a knowledge worker. And also, we suggest the social semantic cloud of tags (SCOT) ontology to represent tag data at a semantic level and combine this ontology in WANT. WANT supports a wide scope of social activities through online mash-up services and interlink resources with desktop and web environments. Our approach provides basic functionalities such as creating, organising and searching knowledge at individual level, as well as enhances social connections among knowledge workers based on their activities.