Abstract
With constant advances in information technology, more and more information is available and users’ information needs are becoming more diverse. Most conventional information systems only attempt to provide information that meets users’ specific interests. In contrast, we are working on ways of discovering information from the viewpoints of both interest and necessity. For example, we are trying to discover complementary information that provides additional knowledge on the users’ topics of interest, not just information that is similar to the topic. In previous work, which was based on extracting topic structures from closed-caption data, we proposed methods of searching for information to complement TV program content; that is, to provide users with more detailed information or different viewpoints. In this paper, we focus on the features of text streams (closed-caption data, etc.) and propose a method for context-sensitive retrieval of complementary information. We modified our topic-structure model for content representation and consider the “context” of a text stream in searching for complementary information. The “context” of the text stream is considered to be a series of topic structures. Based on such kind of context, we propose methods of searching for complementary information for TV programs, including query-type selection, query modification, and computation of the degree of complementarity. The experiment results showed that, comparing to our previous methods, the context-sensitive method could provide more additional information and avoid information overlap.
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References
Henzinger, M., Chang, B.-W., Milch, B., Brin, S.: Query-free news search. In: Proc. of WWW 2003 (2003)
Ma, Q., Tanaka, K.: Topic-Structure Based Complementary Information Retrieval for Information Augmentation. In: Yu, J.X., Lin, X., Lu, H., Zhang, Y. (eds.) APWeb 2004. LNCS, vol. 3007, pp. 608–619. Springer, Heidelberg (2004)
Ma, Q., Tanaka, K.: Topic-structure-based query-free web retrieval mechanism for information integration of Web and TV programs (in Japanese). IPSJ Transactions on Databases 45 (SIG 10) (TOD23), 18–36 (2004)
Ma, Q., Nadamoto, A., Tanaka, K.: Complementary information retrieval for cross-media news contents. In: Proc. of ACM MMDB 2004, pp. 35–44 (2004)
TopicMap.org (2005), http://www.topicmap.org
Wayne, C.L.: Multilingual topic detection and tracking: Successful research enabled by corpora and evaluation. In: Proc. of LREC 2000, pp. 1487–1494 (2000)
Zloof, M.: Query-by-example: A data base language. IBM Systems Journal 16(4), 324–343 (1977)
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© 2005 Springer-Verlag Berlin Heidelberg
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Ma, Q., Tanaka, K. (2005). Context-Sensitive Complementary Information Retrieval for Text Stream. In: Andersen, K.V., Debenham, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2005. Lecture Notes in Computer Science, vol 3588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546924_46
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DOI: https://doi.org/10.1007/11546924_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28566-3
Online ISBN: 978-3-540-31729-6
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