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In this paper we describe the concept of Federated Information Sharing Communities (FISC), and associated architecture, which provide a way for organisations, distributed workgroups and individuals to build up a federated community based on their common interests over the World Wide Web. To support communities, we develop capabilities that go beyond the generic retrieval of documents to include the ability to retrieve people, their interests and inter-relationships. We focus on providing social awareness "in the large" to help users understand the members within a community and the relationships between them. Within the FISC framework, we provide viewpoint retrieval to enable a user to construct visual contextual views of the community from the perspective of any community member. To evaluate these ideas we develop test beds to compare individual component technologies such as user and group profile construction and similarity matching, and we develop prototypes to explore the broader architecture and usage issues.
@inproceedings{1009126, author = {Bicheng Liu and David J. Harper and Stuart Watt}, title = {Supporting federated information sharing communities}, booktitle = {SIGIR '04: Proceedings of the 27th annual international conference on Research and development in information retrieval}, year = {2004}, isbn = {1-58113-881-4}, pages = {572--573}, location = {Sheffield, United Kingdom}, doi = {http://doi.acm.org/10.1145/1008992.1009126}, publisher = {ACM Press}, }  ©2005 Association for Computing Machinery |
