Horting hatches an egg: a new graph-theoretic approach to collaborative filtering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Expertise recommender: a flexible recommendation system and architecture
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
On the recommending of citations for research papers
CSCW '02 Proceedings of the 2002 ACM conference on Computer supported cooperative work
A graph model for E-commerce recommender systems
Journal of the American Society for Information Science and Technology
IEEE Transactions on Knowledge and Data Engineering
Perceptions of visualizing personal mobile communication patterns
Proceedings of the 9th International Conference on Mobile and Ubiquitous Multimedia
Knowledge sharing in dynamic virtual enterprises: A socio-technological perspective
Knowledge-Based Systems
Constructing expert profiles over time for skills management and expert finding
i-KNOW '11 Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies
Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems
Evidence of community structure in Biomedical Research Grant Collaborations
Journal of Biomedical Informatics
Inferring and validating skills and competencies over time
Applied Ontology
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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.