Towards a Generalised Framework for Behaviour Insight Mining

Allmin Susaiyah, Ehud Reiter, Rim Helaoui, Milan Petkovi, Aki Härmä

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

1 Citation (Scopus)

Abstract

A behaviour insight is a statement that explains the behaviour of a user’s activity or a system’s performance under certain conditions. Care must be taken to deliver insights in a way that is useful to the user. Mining for such insights and generating text to communicate about those is a complicated process and there is a need for standardisation to ensure it is done properly. In this work, we lay down the foundation towards a generalised behaviour insight mining framework based on our previous experiences in developing them and express our views on how it can be adopted in a wide range of applications such as Sleep, Marketing, Medical Image Diagnosis and clinical workflow management.
Original languageEnglish
Title of host publicationProceedings of the First Workshop on Smart Personal Health Interfaces, SmartPhil 2020
EditorsSergio Consoli, Diego Reforgiato Recupero, Daniele Riboni
PublisherACM
Pages92-99
Number of pages8
Volume2596
ISBN (Electronic)978-1-4503-7513-9
Publication statusPublished - 17 Mar 2020
EventSmartPHIL: 1st Workshop on Smart Personal Health Interfaces - Cagliari, Italy
Duration: 17 Mar 202020 Mar 2020

Publication series

NameCEUR Workshop Proceedings
PublisherCEUR-WS
Volume2596
ISSN (Electronic)1613-0073

Conference

ConferenceSmartPHIL
Country/TerritoryItaly
CityCagliari
Period17/03/2020/03/20

Bibliographical note

Proceedings of the First Workshop on Smart Personal Health Interfaces co-located with 25th International Conference on Intelligent User Interfaces (IUI 2020) Cagliari, Italy, March 17, 2020.

This work was supported by the Horizon H2020 Marie Sklodowska-Curie Actions Initial Training Network European Industrial Doctorates project under grant agreement No. 812882 (PhilHumans). The authors would like to acknowledge the CLAN reading group at the University of Aberdeen for their valuable feedback and discussions that greatly helped this work.

Keywords

  • data-to-text system
  • behaviour-insight-mining
  • behaviour-change-support-system

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