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Case Study of Data Mining Mutual Engagement

Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)

Human Computer Interaction Conference

4 - 6 July 2018

Creativity, Creativity Support Tools, Mutual Engagement, Data Mining, Evaluation, Interaction Corpus

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      Abstract

      This paper presents a case study of using conventional Data Mining techniques to identify clusters of creative contributions made by users in a collaborative music making system. Results of the clustering suggest that when people mutually engage with each other they tend to converge on similar creative contributions, whereas smaller clusters may indicate higher quality contributions. We also show how we used Data Mining to discriminate between kinds of creative contributions including: complex melodic structures, simple melodic structures, musical motifs, and rhythmical contributions. Our use of Data Mining does not require direct interaction with users and so it may be useful in real-world study contexts.

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      Social influence analysis in large-scale networks

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        Creativity support tools: accelerating discovery and innovation

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          Unsupervised Clickstream Clustering for User Behavior Analysis

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            Author and article information

            Affiliations
            Queen Mary University of London

            London, E1 4NS. UK
            Contributors
            Conference
            July 2018
            July 2018
            : 1-6
            10.14236/ewic/HCI2018.98
            © Bryan-Kinns. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Proceedings of the 32nd International BCS Human Computer Interaction Conference
            HCI
            32
            Belfast, UK
            4 - 6 July 2018
            Electronic Workshops in Computing (eWiC)
            Human Computer Interaction Conference
            Product
            Product Information: 1477-9358 BCS Learning & Development
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

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