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Automatic Advisor for Detecting Summarizable Chat Conversations in Online Instant Messages

  • Fajri KotoEmail author
  • Omar AbdillahEmail author
Conference paper
  • 424 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 463)

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.

Keywords

Chat Summarizable Non-summarizable Feature selection 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Advanced Research LabSamsung R&D Institute IndonesiaJakartaIndonesia

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