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Review of the Main Approaches to Automated Email Answering
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2016 (English)In: New Advances in Information Systems and Technologies: Volume 1 / [ed] Álvaro Rocha, Ana Maria Correia, Hojjat Adeli, Luis Paulo Reis, Marcelo Mendonça Teixeira, Springer, 2016, 135-144 p.Conference paper, Published paper (Refereed)
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Text
Abstract [en]

There were 108.7 billion business emails sent daily in 2014, many of them to contact centers. A number of automated email answering techniques have been explored in order to ease the burden of manual handling of the messages. Most techniques stem from three text retrieval approaches – text categorization by machine learning, statistical text similarity calculation, matching of text patterns and templates. The paper discusses the previous research in automated email answering and compares the techniques.

Place, publisher, year, edition, pages
Springer, 2016. 135-144 p.
Series
Advances in Intelligent Systems and Computing, 444
Keyword [en]
Automated email answering, message answering, email categorization, email classification
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-129736DOI: 10.1007/978-3-319-31232-3_13ISBN: 978-3-319-31231-6 (print)ISBN: 978-3-319-31232-3 (print)OAI: oai:DiVA.org:su-129736DiVA: diva2:923866
Conference
2016 World Conference on Information Systems and Technologies, (WorldCIST’16), Recife, Pernambuco, Brazil, March 22–24, 2016
Available from: 2016-04-27 Created: 2016-04-27 Last updated: 2016-11-10Bibliographically approved

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