Automatic Q.A-Pair Generation for Incident Tickets Handling: An Application of NLP

Mick Lammers, Fons Wijnhoven, Faiza A. Bukhsh, Patrício de Alencar Silva

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Chatbots answer customer questions by mostly manually crafted Question Answer (Q.A.)-pairs. If organizations process vast numbers of questions, manual Q.A. pair generation and maintenance become very ex-pensive and complicated. To reduce cost and increase efficiency, in this study, we propose a low threshold QA-pair generation system that can automatically identify unique problems and their solutions from a large incident ticket dataset of an I.T. Shared Service Center. The system has four components: categorical clustering for structuring the semantic meaning of ticket information, intent identification, action recommendation, and reinforcement learning. For categorical clustering, we use a Latent Semantic Indexing (LSI) algorithm, and for the intent identification, we apply the Latent Dirichlet Allocation (LDA), both Natural Language Processing techniques. The actions are cleaned and clustered and resulting Q.A. pairs are stored in a knowledge base with reinforcement learning capabilities. The system can produce Q.A. pairs from which about 55% are useful and correct. This percentage is likely to in-crease significantly with feedback in its usage stage. By this study, we contribute to a further understanding of the development of automatic service processes.

Original languageEnglish
Title of host publicationEconomics of Grids, Clouds, Systems, and Services
Subtitle of host publication17th International Conference, GECON 2020, Izola, Slovenia, September 15–17, 2020, Revised Selected Papers
EditorsKarim Djemame, José Ángel Bañares, Vlado Stankovski, Jörn Altmann, Orna Agmon Ben-Yehuda, Bruno Tuffin
Place of PublicationCham
PublisherSpringer
Pages15-27
Number of pages13
ISBN (Electronic)978-3-030-63058-4
ISBN (Print)978-3-030-63057-7
DOIs
Publication statusPublished - 2020
Event17th International Conference on the Economics of Grids, Clouds, Systems and Services, GECON 2020 - Online Conference
Duration: 15 Sep 202017 Sep 2020
Conference number: 17
http://2020.gecon-conference.org/

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12441 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on the Economics of Grids, Clouds, Systems and Services, GECON 2020
Abbreviated titleGECON 2020
Period15/09/2017/09/20
Internet address

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