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Ontology-Based Recommendation of Editorial Products

Thanapalasingam, Thiviyan; Osborne, Francesco; Birukou, Aliaksandr and Motta, Enrico (2018). Ontology-Based Recommendation of Editorial Products. In: ISWC 2018: The Semantic Web (Proceedings, Part II) (Vrandečić, Denny; Bontcheva, Kalina; Suárez-Figueroa, Mari Carmen; Presutti, Valentina; Celino, Irene; Sabou, Marta; Kaffee, Lucie-Aimée and Simperl, Elena eds.), Lecture Notes in Computer Science 11137, Springer, pp. 341–358.

DOI (Digital Object Identifier) Link: https://doi.org/10.1007/978-3-030-00668-6_21
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Abstract

Major academic publishers need to be able to analyse their vast catalogue of products and select the best items to be marketed in scientific venues. This is a complex exercise that requires characterising with a high precision the topics of thousands of books and matching them with the interests of the relevant communities. In Springer Nature, this task has been traditionally handled manually by publishing editors. However, the rapid growth in the number of scientific publications and the dynamic nature of the Computer Science landscape has made this solution increasingly inefficient. We have addressed this issue by creating Smart Book Recommender (SBR), an ontology-based recommender system developed by The Open University (OU) in collaboration with Springer Nature, which supports their Computer Science editorial team in selecting the products to market at specific venues. SBR recommends books, journals, and conference proceedings relevant to a conference by taking advantage of a semantically enhanced representation of about 27K editorial products. This is based on the Computer Science Ontology, a very large-scale, automatically generated taxonomy of research areas. SBR also allows users to investigate why a certain publication was suggested by the system. It does so by means of an interactive graph view that displays the topic taxonomy of the recommended editorial product and compares it with the topic-centric characterization of the input conference. An evaluation carried out with seven Springer Nature editors and seven OU researchers has confirmed the effectiveness of the solution.

Item Type: Conference or Workshop Item
Copyright Holders: 2018 Springer Nature
ISBN: 3-030-00667-0, 978-3-030-00667-9
Project Funding Details:
Funded Project NameProject IDFunding Body
Smart Classification and Intelligent Decision Support to Assist Editorial Processes at Springer NatureNot SetSpringer
Extra Information: originally presented at the International Semantic Web Conference 2018, Monterey, California, USA, 8-12 Oct 2018.
Keywords: Recommender Systems; Ontology; User Interface; Scholarly Ontology; Scholarly Data
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Innovation, Knowledge & Development research centre (IKD)
Related URLs:
Item ID: 55516
Depositing User: Thiviyan Thanapalasingam
Date Deposited: 25 Jun 2018 15:43
Last Modified: 02 May 2019 17:10
URI: http://oro.open.ac.uk/id/eprint/55516
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