IEEE Intelligent Systems
Usage patterns of collaborative tagging systems
Journal of Information Science
Proceedings of the 15th international conference on World Wide Web
The Dark Side of the Semantic Web
IEEE Intelligent Systems
Harvesting Wiki Consensus: Using Wikipedia Entries as Vocabulary for Knowledge Management
IEEE Internet Computing
SIOC: an approach to connect web-based communities
International Journal of Web Based Communities
Social semantic cloud of tag: semantic model for social tagging
KES-AMSTA'08 Proceedings of the 2nd KES International conference on Agent and multi-agent systems: technologies and applications
An empirical study on optimizing query transformation on semantic peer-to-peer networks
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Knowledge integration and management in autonomous systems
KFTGA: A tool for tracing knowledge flow and knowledge growth in knowledge sharing environment
Information-Knowledge-Systems Management
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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.