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A New Method of Detecting Time Expressions for E-mail Messages

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2004)

Abstract

Although E-mail systems are one of the most useful communication tools for business, education, etc,. It is very useful filtering supports for users to pick up important messages or to neglect unnecessary messages. This paper presents a method of determining the time priority for E-mail messages. Multi-attribute rules are defined to detect complex time expressions and a set pattern-matching machine is proposed. It enables us to protect missing messages with important time information because the presented method can classify and rank them according to time priority measurement automatically. From the simulation results of determining time priority, the presented pattern-matching method is from about 4 times faster than the traditional string pattern-matching method. From the results of filtering 5,172 sentences, precision and recall of the presented method becomes 95% and 96%, respectively. From the experimental results of determining 10 highest messages among 100 E-mail, filtering time is from 9.7 to 16.6 faster than that of a non-filtering method.

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References

  1. Aho, A.V., Corasick, M.J.: Efficient string matching: An aid to bibliographic search. Communications of the ACM 18(6), 333–340 (1975)

    Article  MATH  MathSciNet  Google Scholar 

  2. Allen, J.F.: Towards a General Theory of Action and Time. Artificial Intelligence 23(2), 123–154 (1984)

    Article  MATH  Google Scholar 

  3. Aoe, J.: An efficient digital search algorithm by using a double-array structure. IEEE Trans. Softw. Engr. SE-15(9), 1066–1077 (1989)

    Article  Google Scholar 

  4. EDR Electronic Dictionary. Japan Electronic Dictionary Research Institute (1995)

    Google Scholar 

  5. Hasegawa, T.: Personalized E-mail Ranking Based on Communication History and Information Extraction. IPS Japan SIG Notes 99-NL-132-3, 12–17 (1999)

    Google Scholar 

  6. Ikehara, S., Ohara, E., Takagi, S.: Natural Language Processing for Japanese Text Revision Support System. Magazine of IPS Japan 34(10), 1249–1258 (1993)

    Google Scholar 

  7. Jensen, C.S., Snodgrass, R.T.: Temporal Data Management. IEEE Transactions on Knowledge and Data Engineering 11(1), 36–44 (1999)

    Article  Google Scholar 

  8. Mani, I.: Automatic Summarization. John Benjamins Publishing Company, Amsterdam (2001)

    MATH  Google Scholar 

  9. Matoba, K., Ikehara, S., Murakami, J.: Semantic Analysis of Time Expressions for Japanese to English Machine Translation. IPS Japan SIG Notes 01-NL-146-9, 53–60 (2001)

    Google Scholar 

  10. Mizobuchi, S., Morita, K., Fuketa, M., Aoe, J.: Conceptual and Quantitative Representations of Time Expressions. Journal of Computer Processing of Oriental Languages 13(4), 313–331 (2000)

    Article  Google Scholar 

  11. K. Tamano & Y. Matsumoto. A study of constraint based description of temporal structure. IPS Japan SIG Notes, (in Japanese), 96-NL-115-2, 9-14 (1996)

    Google Scholar 

  12. Tamura, N.: Formalization and Implementation of Summary Generation. Journal of JSAI 4(2), 196–206 (1989)

    Google Scholar 

  13. Terenziani, P.: Integrating Calendar Dates and Qualitative Temporal Constraints in the Treatment of Periodic Events. IEEE Transactions on Knowledge and Data Engineering 9(5), 763–783 (1997)

    Article  Google Scholar 

  14. Tojo, S.: Generation of Inter-Affair Relations Based on Temporal Features of Process, State, and Event. Journal of JSAI, (in Japan) 10(6), 904–912 (1995)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Sumitomo, T., Kadoya, Y., Atlam, Es., Morita, K., Kashiji, S., Aoe, Ji. (2004). A New Method of Detecting Time Expressions for E-mail Messages. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30132-5_76

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  • DOI: https://doi.org/10.1007/978-3-540-30132-5_76

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23318-3

  • Online ISBN: 978-3-540-30132-5

  • eBook Packages: Springer Book Archive

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