People recommendation based on aggregated bidirectional intentions in social network site
PKAW'10 Proceedings of the 11th international conference on Knowledge management and acquisition for smart systems and services
| Hi-index | 0.00 |
Recent advances in Web 2.0 and cyberinfrastructure have enabled new levels of interactions and interconnections among individuals, documents, data, analytic tools and concepts. For communities to be more effective in using these resources, it is even more crucial that they have tools help them identify the right expertise or knowledge resources from within this large "multidimensional network." Cyberinfrastructure Knowledge Networks on the Web (CI-KNOW) is a suite of Web-based tools that facilitates discovery of resources within communities. CKNOW facilitates discovery by implementing a network recommendation system that incorporates social motivations for why we create, maintain, and dissolve our knowledge network ties. The network data is captured by automated harvesting of digital resources using Web crawlers, text miners, tagging tools that automatically generate community-oriented metadata, and scientometric data such as co-authorship and citations. Based on this knowledge network, the CI-KNOW recommender system produces personalized search results through two steps: identify matching entities according to their metadata and network statistics and select the best fits according to requester's perspectives and connections in the social network. Integrated with community Web portals, CI-KNOW navigation and auditing portlets provide analysis and visualization tools for community members and serves as a research testbed to test social networks models about individuals' motivations for seeking expertise from specific resources (people documents, datasets, etc.). As a proof-of-concept, this paper demonstrates how CI-KNOW has been integrated with the NCI-supported Tobacco Informatics Grid (TobIG) to facilitate knowledge sharing in the tobacco control research community.