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Automatic summarisation of discussion fora

Published online by Cambridge University Press:  24 March 2010

ALMER S. TIGELAAR ,
RIEKS OP DEN AKKER  and
DJOERD HIEMSTRA
ALMER S. TIGELAAR
Affiliation:
Database and Human Media Interaction Groups, University of Twente, The Netherlands e-mail: a.s.tigelaar@cs.utwente.nl, infrieks@cs.utwente.nl, hiemstra@cs.utwente.nl
RIEKS OP DEN AKKER
Affiliation:
Database and Human Media Interaction Groups, University of Twente, The Netherlands e-mail: a.s.tigelaar@cs.utwente.nl, infrieks@cs.utwente.nl, hiemstra@cs.utwente.nl
DJOERD HIEMSTRA
Affiliation:
Database and Human Media Interaction Groups, University of Twente, The Netherlands e-mail: a.s.tigelaar@cs.utwente.nl, infrieks@cs.utwente.nl, hiemstra@cs.utwente.nl
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Abstract

Web-based discussion fora proliferate on the Internet. These fora consist of threads about specific matters. Existing forum search facilities provide an easy way for finding threads of interest. However, understanding the content of threads is not always trivial. This problem becomes more pressing as threads become longer. It frustrates users that are looking for specific information and also makes it more difficult to make valuable contributions to a discussion. We postulate that having a concise summary of a thread would greatly help forum users. But, how would we best create such summaries? In this paper, we present an automated method of summarising threads in discussion fora. Compared with summarisation of unstructured texts and spoken dialogues, the structural characteristics of threads give important advantages. We studied how to best exploit these characteristics. Messages in threads contain both explicit and implicit references to each other and are structured. Therefore, we term the threads hierarchical dialogues. Our proposed summarisation algorithm produces one summary of an hierarchical dialogue by ‘cherry-picking’ sentences out of the original messages that make up a thread. We try to select sentences usable for obtaining an overview of the discussion. Our method is built around a set of heuristics based on observations of real fora discussions. The data used for this research was in Dutch, but the developed method equally applies to other languages. We evaluated our approach using a prototype. Users judged our summariser as very useful, half of them indicating they would use it regularly or always when visiting fora.

Type
Papers
Information
Natural Language Engineering , Volume 16 , Issue 2 , April 2010 , pp. 161 - 192
Copyright
Copyright © Cambridge University Press 2010

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