Skip to main content

Automatic Advisor for Detecting Summarizable Chat Conversations in Online Instant Messages

  • Conference paper
  • First Online:
Recent Advances in Information and Communication Technology 2016

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 463))

  • 518 Accesses

Abstract

In this paper, we report the first work ever of detecting the summarizable chat conversation in order to improve the quality of summarization and system performance, especially in real time server-based system like online instant messaging. Summarizable chat conversation means that the document assessed could produce a meaningful summary for human. Our study intends to answer the question: what are the characteristics of a summarizable chat and how to distinguish it with non-summarizable chat conversation. To conduct the experiment, corpora of 536 chat conversations was constructed manually. Technically, we used 19 attributes and grouped them by feature sets of (1) chat attribute, (2) lexical, and (3) Rapid Automatic Keyword Extraction (RAKE). As result, our work reveals that the features can classify summarizable chat by 78.36 % as our highest accuracy, performed by feature selection with SVM.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Sood, A., Mohamed, T.P., Varma, V.: Topic-focused summarization of chat conversations. In: Advances in Information Retrieval, pp. 800–803 (2013)

    Google Scholar 

  2. Uthus, D.C., Aha, D.W.: Plans toward automated chat summarization. In: Proceedings of the Workshop on Automatic Summarization for Different Genres, Media, and Languages. ACL (2011)

    Google Scholar 

  3. Koto, F., Sakriani S., Neubig, G., Toda, T., Adriani, M., Nakamura, S.: The use of semantic and acoustic features for open-domain TED talk summarization. In: Proceedings of The 6th Asia Pacific Signal and Information Processing Association (APSIPA). Siem Reap, Cambodia (2014)

    Google Scholar 

  4. Werry, C.C.: In: Linguistic and Interactional Features of Internet Relay Chat, pp. 47–64 (1996)

    Google Scholar 

  5. Hering, S.C.: Interactional coherence in CMC. In: Proceedings of the Thirty-Second Annual Hawaii International Conference on System Sciences (1999)

    Google Scholar 

  6. Hering, S.C.: Computer-mediated conversation: introduction and overview. In: Language@ Internet (2010)

    Google Scholar 

  7. Zhou, L., Hovy, E.: Digesting virtual “geek” culture: the summarization of technical Internet Relay Chats. In: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, pp. 298–305. ACL (2005)

    Google Scholar 

  8. Zechner, K.: Automatic summarization of open-domain multiparty dialogues in diverse genres. Comput. Linguist. 28(4), 447–485 (2002)

    Article  Google Scholar 

  9. Murray, G., Renals, S., Carletta, J., Moore, J.: Evaluating automatic summaries of meeting recordings. In: Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization, pp. 33–40. ACL (2005)

    Google Scholar 

  10. Cohen, J.: A coefficient of agreement for nominal scales. Educ. Psychol. Meas. 20(1), 37–46 (1960)

    Article  Google Scholar 

  11. Altman, D.G.: Practical Statistics for Medical research, vol. 20(1). Chapman Hall/CRC Press, London (1990)

    Google Scholar 

  12. Berry, M.W., Kogan, J.: “Text Mining”: Applications and Theory. Wiley, West Sussex, PO19 8SQ, UK (2010)

    Google Scholar 

  13. Akthar, F., Hahne, C.: RapidMiner 5 Operator Reference. In: Rapid-I GmbH (2012)

    Google Scholar 

  14. Montgomery, D.C., Peck, E.A., Vining, G.G.: Introduction to Linear Regression Analysis, vol. 821. Wiley, West Sussex, PO19 8SQ, UK (2012)

    Google Scholar 

  15. Lewis, D.D.: Naive (Bayes) at forty: the independence assumption in information retrieval. In: Educational and Psychological Machine learning: ECML-98, pp. 4–15. Springer, Berlin, Heidelberg (1998)

    Google Scholar 

  16. Fu, L.M.: Neural Network in Computer Intelligence. MIT-Press, McGraw-Hill International Edition (1994)

    Google Scholar 

  17. Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods. Cambridge university press (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Fajri Koto or Omar Abdillah .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Koto, F., Abdillah, O. (2016). Automatic Advisor for Detecting Summarizable Chat Conversations in Online Instant Messages. In: Meesad, P., Boonkrong, S., Unger, H. (eds) Recent Advances in Information and Communication Technology 2016. Advances in Intelligent Systems and Computing, vol 463. Springer, Cham. https://doi.org/10.1007/978-3-319-40415-8_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-40415-8_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40414-1

  • Online ISBN: 978-3-319-40415-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics