Quotation Vakulenko, Svitlana, Revoredo, Kate, Di Ciccio, Claudio, de Rijke, Maarten. 2019. QRFA: A Data-Driven Model of Information-Seeking Dialogues. In 41st European Conference on IR Research, ECIR 2019, Cologne, Germany, April 14–18, 2019, Proceedings, Part I, Hrsg. Leif Azzopardi, Benno Stein, Norbert Fuhr, Philipp Mayr, Claudia Hauff, Djoerd Hiemstra, 541-557. Cologne, Germany: Springer.


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Abstract

Understanding the structure of interaction processes helps us to improve information-seeking dialogue systems. Analyzing an interaction process boils down to discovering patterns in sequences of alternating utterances exchanged between a user and an agent. Process mining techniques have been successfully applied to analyze structured event logs, discovering the underlying process models or evaluating whether the observed behavior is in conformance with the known process. In this paper, we apply process mining techniques to discover patterns in conversational transcripts and extract a new model of information-seeking dialogues, QRFA, for Query, Request, Feedback, Answer. Our results are grounded in an empirical evaluation across multiple conversational datasets from different domains, which was never attempted before. We show that the QRFA model better reflects conversation flows observed in real information-seeking conversations than models proposed previously. Moreover, QRFA allows us to identify malfunctioning in dialogue system transcripts as deviations from the expected conversation flow described by the model via conformance analysis.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Contribution to conference proceedings
Language English
Title QRFA: A Data-Driven Model of Information-Seeking Dialogues
Title of whole publication 41st European Conference on IR Research, ECIR 2019, Cologne, Germany, April 14–18, 2019, Proceedings, Part I
Editor Leif Azzopardi, Benno Stein, Norbert Fuhr, Philipp Mayr, Claudia Hauff, Djoerd Hiemstra
Page from 541
Page to 557
Location Cologne, Germany
Publisher Springer
Year 2019
URL https://doi.org/10.1007/978-3-030-15712-8_35
Open Access N

Associations

Projects
RISE_BPM
Open Data for Local Communities
Cyber-Physical Social Systems for City-wide Infrastructures
People
Vakulenko, Svitlana (Details)
Di Ciccio, Claudio (Details)
External
de Rijke, Maarten (University of Amsterdam, Netherlands)
Revoredo, Kate (Federal University of the State of Rio de Janeiro, Brazil)
Organization
Applied Information Technology with Focus on IT in Organization (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
1105 Computer software (Details)
1108 Informatics (Details)
1109 Information and data processing (Details)
1122 Artificial intelligence (Details)
1161 Human-computer interaction (Details)
5306 Business data processing (Details)
5367 Management information systems (Details)
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