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OSIBR: Ontology Focused Semantic Intelligence Approach for Book Recommendation

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Digital Technologies and Applications (ICDTA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 454))

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Abstract

With the dawn of digital books on the web, finding reliable book suggestions has become a complicated question, and several significant machine learning algorithms were developed to address such requests. Also, there exists a problem of the prevailing recommendation system not presenting a well fit to the semantically designed nature of the world wide web. Moreover, due to the vast digitization of books, a plethora of the old book discovery strategic approaches is intended for physical selection only. Therefore, research interest is increasing in the innovative approach to search, browse, and use the recommendation engine. In this paper, an ontology focused semantic intelligence approach for the book recommendation is proposed using Jaccard similarity, NPMI, and Kullback Leibler divergence with the optimization done by the Krill Herd algorithm. The proposed system OSIBR reaches an overall Precision and Accuracy of 94.16% and 95.55% respectively and with the highest Normalized Discounted Cumulative Gain (nDCG) of 0.96.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology, Tiruchirappalli, India

    Gerard Deepak

  2. SRM Institute of Science and Technology, Ramapuram, Chennai, India

    Ramanathan Nachiappan

Authors
  1. Ramanathan Nachiappan
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  2. Gerard Deepak
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Correspondence to Gerard Deepak .

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Editors and Affiliations

  1. Ecole Nationale des Sciences Appliquées, Fez, Morocco

    Saad Motahhir

  2. Faculty of Sciences, Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Badre Bossoufi

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Nachiappan, R., Deepak, G. (2022). OSIBR: Ontology Focused Semantic Intelligence Approach for Book Recommendation. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2022. Lecture Notes in Networks and Systems, vol 454. Springer, Cham. https://doi.org/10.1007/978-3-031-01942-5_40

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