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Authors: Arseny Korotaev 1 and Lyudmila Lyadova 2

Affiliations: 1 Department of Computer Science, Perm State National Research University, Perm and Russia ; 2 Department of Information Technologies in Business, National Research University Higher School of Economics, Perm and Russia

Keyword(s): Deep Learning, Knowledge-based Recommender System, Ontology, Customization, GRU.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Domain Analysis and Modeling ; Human-Machine Cooperation ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Symbolic Systems

Abstract: The GRU-based recurrent neural networks (RNN) for constructing recommendation systems are proposed. Such systems are mainly developed by large companies for specific domains. At the same time, small companies don’t have the necessary resources to develop their own unique systems. Therefore, they need universal recommendation system (or recommender platform) automatically customized for a specific domain. This system allows to develop own recommendation system from scratch for companies whose services are under development. The RNN-based approach is proposed for session-based recommendation with automatically modelling of the domain. This approach is based on the content analysis of the web sites. Several modifications to classic RNNs such as a ranking loss function that make it more viable for this specific problem are considered. General scheme of the approach and architecture of the recommendation system based on proposed scheme are described in this paper.

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Paper citation in several formats:
Korotaev, A. and Lyadova, L. (2018). Method for the Development of Recommendation Systems, Customizable to Domains, with Deep GRU Network. In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KEOD; ISBN 978-989-758-330-8; ISSN 2184-3228, SciTePress, pages 231-236. DOI: 10.5220/0006933302310236

@conference{keod18,
author={Arseny Korotaev. and Lyudmila Lyadova.},
title={Method for the Development of Recommendation Systems, Customizable to Domains, with Deep GRU Network},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KEOD},
year={2018},
pages={231-236},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006933302310236},
isbn={978-989-758-330-8},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KEOD
TI - Method for the Development of Recommendation Systems, Customizable to Domains, with Deep GRU Network
SN - 978-989-758-330-8
IS - 2184-3228
AU - Korotaev, A.
AU - Lyadova, L.
PY - 2018
SP - 231
EP - 236
DO - 10.5220/0006933302310236
PB - SciTePress