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An Approach Towards Human Centric Automatic Ontology Design

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Advances in Data Computing, Communication and Security

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 106))

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Abstract

Given the magnanimous amount of data that the web stores and with the evolution of semantic web, appropriate techniques for management of semantic information become vital. The time of accessing the required piece of information defines the efficiency of a system. Ontologies play a very important role in defining and organizing the information segments of a domain, which in turn help improve the efficiency of retrieval of required information. In this paper, the focus is to densify and generate improved ontologies from adopted seed-domain ontologies by incorporating a framework that utilizes a multisegmented methodology involving the LSTM model for classification followed by the cuckoo search metaheuristic optimization algorithm and semantic similarity computation approaches such as Kullback–Leibler divergence and SemantoSim measure—a child approach of the commonly used WebPMI, to hold context and enrich the relatedness in the improvised ontologies. This human centric approach also implements various logic rules and agents to delicately handle the semantic data at the same time preserve its integrity. Domains adopted for the purpose of experimentation are ensured to be from diverse real-world topics. The efficiency of the proposed model is seen to be higher than the adopted baseline, and the former supported with an accuracy of 96.12% and a false discovery rate of 0.043, therefore, exhibiting clean success of experimentation.

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Author information

Authors and Affiliations

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

    S. Manaswini

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

    Gerard Deepak & A. Santhanavijayan

Authors
  1. S. Manaswini
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  2. Gerard Deepak
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  3. A. Santhanavijayan
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Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, National Institute of Technology, Kurukshetra, Kurukshetra, India

    Pankaj Verma

  2. Department of Electronics and Communication Engineering, National Institute of Technology, Kurukshetra, Kurukshetra, India

    Chhagan Charan

  3. Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON, Canada

    Xavier Fernando

  4. Department of Electrical and Computer Engineering, Oakland University, Rochester, MI, USA

    Subramaniam Ganesan

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Manaswini, S., Deepak, G., Santhanavijayan, A. (2022). An Approach Towards Human Centric Automatic Ontology Design. In: Verma, P., Charan, C., Fernando, X., Ganesan, S. (eds) Advances in Data Computing, Communication and Security. Lecture Notes on Data Engineering and Communications Technologies, vol 106. Springer, Singapore. https://doi.org/10.1007/978-981-16-8403-6_26

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