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Authors: Hans Friedrich Witschel and Andreas Martin

Affiliation: FHNW University of Applied Sciences and Arts Northwestern Switzerland, CH-4600 Olten and Switzerland

ISBN: 978-989-758-330-8

Keyword(s): Recommender Systems, Knowledge Representation, Random Walks.

Abstract: We explore the use of recommender systems in business scenarios such as consultancy. In these situations, apart from personal preferences of users, knowledge about objective business-driven criteria plays a role. We investigate strategies for representing and incorporating such knowledge into data-driven recommenders. As a baseline, we choose a robust and flexible paradigm that is based on a simple graph-based representation of past customer cases and choices, in combination with biased random walks. On a real data set from a business intelligence consultancy firm, we study how the incorporation of two important types of explicit human knowledge – namely taxonomic and associative knowledge – impacts the effectiveness of a data-driven recommender. Our results show no consistent improvement for taxonomic knowledge, but quite substantial and significant gains when using associative knowledge.

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Paper citation in several formats:
Witschel, H. and Martin, A. (2018). Random Walks on Human Knowledge: Incorporating Human Knowledge into Data-Driven Recommenders.In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS, ISBN 978-989-758-330-8, pages 63-72. DOI: 10.5220/0006893900630072

@conference{kmis18,
author={Hans Friedrich Witschel. and Andreas Martin.},
title={Random Walks on Human Knowledge: Incorporating Human Knowledge into Data-Driven Recommenders},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS,},
year={2018},
pages={63-72},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006893900630072},
isbn={978-989-758-330-8},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS,
TI - Random Walks on Human Knowledge: Incorporating Human Knowledge into Data-Driven Recommenders
SN - 978-989-758-330-8
AU - Witschel, H.
AU - Martin, A.
PY - 2018
SP - 63
EP - 72
DO - 10.5220/0006893900630072

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