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Smart Book Recommender: A Semantic Recommendation Engine for Editorial Products

Osborne, Francesco; Thanapalasingam, Thiviyan; Salatino, Angelo; Birukou, Aliaksandr and Motta, Enrico (2017). Smart Book Recommender: A Semantic Recommendation Engine for Editorial Products. In: International Semantic Web Conference (ISWC) 2017, 21-25 Oct 2017, Vienna, Austria.

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Academic publishers, such as Springer Nature, need to constantly make informed decisions about how and where to market their editorial products. In the field of Computer Science (CS), it is particularly critical to assess which books will be of interest to the attendees of a conference. Typically, these items are manually chosen by publishing editors, on the basis of their personal experience. To make this process both faster and more robust we have developed the Smart Book Recommender (SBR), a semantic application designed to support the Springer Nature editorial team in promoting their publications at CS venues. SBR takes as input the proceedings of a conference and suggests books, journals, and other conference proceedings which are likely to be relevant to the attendees of the conference in question. It does so by taking advantage of a semantic representation of topics, which builds on a very large ontology of Computer Science topics; characterizing Springer Nature books as distributions of semantic topics; and approaching the problem as one of semantic matching between such distributions of semantic topics.

Item Type: Conference or Workshop Item
Keywords: Scholarly Data;Recommendation Systems;Ontology;Bibliographic Data;Scholarly Ontologies
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: Centre for Research in Computing (CRC)
Item ID: 50892
Depositing User: Francesco Osborne
Date Deposited: 22 Sep 2017 15:19
Last Modified: 03 May 2019 07:28
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These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

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