A structure-based approach for multimedia information filtering
While multimedia documents are sequentially presented to users, an information filtering (IF) system is useful to achieve a good retrieval performance in terms of both quality and efficiency. Conventional approaches for designing an IF system are based on the user's evaluation on information relevance degree (IRD), but ignore other attributes in system design such as relative importance of the data in a collection of multimedia documents. In this paper, we aim at developing a framework of designing structure-based multimedia IF systems, which incorporates the characteristics of the importance and relevance of multimedia documents. A method of calculating the values of relative importance degree of multimedia documents is proposed. Furthermore, these values are combined into the IRD of multimedia documents to improve the representation of user profiles. An illustrative example is given to demonstrate the proposed techniques.
KeywordsMultimedia documents Display algorithms Search and retrieval Information filtering
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- 2.Freeman LC (1978) Centrality in social networks. I. Conceptual clarification. Social networks. Cambridge University Press 1:215–239Google Scholar
- 4.Kleinberg J (1998) Authoritative sources in a hyperlinked environment, Proc. 9th ACM-SIAM Symposium on Discrete AlgorithmsGoogle Scholar
- 5.Linda S (1994) Relevance and information behaviour. Annual Review Information Science Technology (ARIST) 29:3–48Google Scholar
- 10.Page L, Brin S, Motwani R, Winograd T (1998) The pagerank citation ranking: bringing order to the web, Stanford Digital Library Technologies ProjectGoogle Scholar
- 11.Robertson SF (1977) The probability ranking principle. Journal of Multimedia Documentation 294–304Google Scholar
- 12.Rocchio J (1971) Relevance feedback in information retrieval. 313–323Google Scholar
- 13.Scott, J (2000) Social network analysis: a handbook. Sage, LondonGoogle Scholar
- 14.Wasserman S, Katherine F (1994) Social network analysis: methods and applicationsGoogle Scholar