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ISBRNM: Integrative Approach for Semantically Driven Blog Recommendation Using Novel Measures

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Digital Technologies and Applications (ICDTA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 455))

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Abstract

In the present-day time, Blog recommendation is of great importance as the Internet grows, individuals face immense amounts of information. Due to the rise of microblogs, it has become a vital tool to provide accurate and timely information. Thereby, in recent times of Semantic Web, blog recommendation is one of the crucial aspects to search and shortlist the user preferred relevant content which is of extreme value. This paper proposes an integrative approach for Semantically driven Blog recommendation using Latent Dirichlet Allocation for the Natural Language Processing, Gated Recurrent Units as a classifier and semantic similarities are computed using Normalized Pointwise Mutual Index, Normalized Google Distance and Theil index which is classified using the Moth Flame Optimization algorithm. The experiments have been conducted for the Blog Authorship corpus and the accuracy percentage of 95.85% is achieved.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, India

    M. Anirudh

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

    Gerard Deepak

Authors
  1. M. Anirudh
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  2. Gerard Deepak
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Corresponding author

Correspondence to Gerard Deepak .

Editor information

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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Anirudh, M., Deepak, G. (2022). ISBRNM: Integrative Approach for Semantically Driven Blog Recommendation Using Novel Measures. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2022. Lecture Notes in Networks and Systems, vol 455. Springer, Cham. https://doi.org/10.1007/978-3-031-02447-4_2

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