Paper Info
Title
CI-KNOW: recommendation based on social networks
Abstract
Digital media and communication networks have become an important cyberinfrastructure to enable new levels of interactions in organizations and communities. A complicated knowledge network of individuals, documents, data, concepts, and their interconnections forms a virtual knowledge repository. To be more effective in using these resources, knowledge discovery tools are crucial for an organization and individual users to identify the right expertise or knowledge resources from 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. CI-KNOW implements 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 social networks. 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 examine social theories on individuals' motivations for seeking expertise from specific resources (people, documents, datasets, and etc.). As a proof-of-concept, this paper demonstrates how CI-KNOW, integrated with the NCI-supported Tobacco Informatics Grid (TobIG), facilitates knowledge sharing in the tobacco control research community.
Year
DOI
Venue
2008
10.1145/1367832.1367900
DG.O
Keywords
DocType
Citations 
knowledge discovery tool,network recommendation system,ci-know navigation,multidimensional network,network data,knowledge network tie,knowledge resource,social network,complicated knowledge network,knowledge network,ci-know recommender system,web crawler,facilitates knowledge sharing,communication network,network statistic,knowledge discovery,community,social network analysis,recommender system
Conference
8
PageRank 
References 
Authors
0.62
7
3
Name
Order
Citations
PageRank
Yun Huang111811.29
Noshir S. Contractor250761.05
York Yao380.62