DLAIIRMar 24, 2021

Ontology-Based Recommendation of Editorial Products

arXiv:2103.13526v136 citations
Originality Synthesis-oriented
AI Analysis

This addresses inefficiencies for major academic publishers like Springer Nature in matching editorial products to conferences, but it is incremental as it applies existing ontology methods to a specific domain.

The paper tackles the problem of manually selecting academic publications for marketing at scientific venues by developing an ontology-based recommender system, which was evaluated with 14 users and confirmed effective.

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.

Foundations

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