Dunne, Jonathan and Malone, David (2018) Hello & Goodbye: Conversation Boundary Identification Using Text Classification. In: 29th Irish Signals and Systems Conference, 21-22 June 2018, Queen's University Belfast.

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Abstract

One of the main challenges in discourse analysis is the process of segmenting text into meaningful topic segments. While this problem has been studied over the past thirty years, previous topic segmentation studies ignore crucial elements of a conversation: an opening and closing remark. Our motivation to revisit this problem space is the rise of instant message usage. We consider the problem of topic segmentation as a machine learning classification one. Using both enterprise and open source datasets, we address the question as to whether a machine learning algorithm can be trained to identify salutations and valedictions within multi-party real-time chat conversations. Our results show that both Naive Bayes (NB) and Support Vector Machine (SVM) algorithms provide a reasonable degree of precision(mean F1 score: 0.58).

Item Type:	Conference or Workshop Item (Paper)
Keywords:	text classification; discourse analysis; segmenting text; machine learning; algorithms; Naive Bayes; Support Vector Machine;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Science and Engineering > Mathematics and Statistics
Item ID:	13360
Depositing User:	Dr. David Malone
Date Deposited:	02 Oct 2020 14:21
Refereed:	Yes
URI:
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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