A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions

Azlan Yusof, Moamin A. Mahmoud, Mohd Sharifuddin Ahmad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Universities are continuously attempting to attract more customers via social media sites such as Facebook. However, the problem of inadequate marketing still remains. A prominent issue here is that the strategy of using different resources and contents to deliver information about the universities to their customers is inefficient because it does not solve the problem of identifying and delivering visitors' preferences. Consequently, we propose a conceptual model of a dynamic and self-Adaptive website design utilizing the concept of multi-Agent semantics web approach to include an intelligent strategic marketing for the website. The proposed model consists of five components which are, Agent Generator System; Preferences Model Base; Grouping Process; Ontology Library; Semantic Web; and Rendering Engine. The outcome of this paper is a Conceptual Multi-Agent Semantic Web Model that could be exploited to design a highly dynamic website that is expected to meet visitors' preferences.

Original languageEnglish
Title of host publication2nd International Symposium on Agent, Multi-Agent Systems and Robotics, ISAMSR 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages133-138
Number of pages6
ISBN (Electronic)9781509051502
DOIs
Publication statusPublished - 06 Jan 2017
Event2nd International Symposium on Agent, Multi-Agent Systems and Robotics, ISAMSR 2016 - Bangi, Malaysia
Duration: 23 Aug 201624 Aug 2016

Other

Other2nd International Symposium on Agent, Multi-Agent Systems and Robotics, ISAMSR 2016
CountryMalaysia
CityBangi
Period23/08/1624/08/16

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Semantic Web
Websites
Marketing
Ontology
Engines

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications

Cite this

Yusof, A., A. Mahmoud, M., & Ahmad, M. S. (2017). A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions. In 2nd International Symposium on Agent, Multi-Agent Systems and Robotics, ISAMSR 2016 (pp. 133-138). [7810016] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISAMSR.2016.7810016
Yusof, Azlan ; A. Mahmoud, Moamin ; Ahmad, Mohd Sharifuddin. / A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions. 2nd International Symposium on Agent, Multi-Agent Systems and Robotics, ISAMSR 2016. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 133-138
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Yusof, A, A. Mahmoud, M & Ahmad, MS 2017, A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions. in 2nd International Symposium on Agent, Multi-Agent Systems and Robotics, ISAMSR 2016., 7810016, Institute of Electrical and Electronics Engineers Inc., pp. 133-138, 2nd International Symposium on Agent, Multi-Agent Systems and Robotics, ISAMSR 2016, Bangi, Malaysia, 23/08/16. https://doi.org/10.1109/ISAMSR.2016.7810016

A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions. / Yusof, Azlan; A. Mahmoud, Moamin; Ahmad, Mohd Sharifuddin.

2nd International Symposium on Agent, Multi-Agent Systems and Robotics, ISAMSR 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 133-138 7810016.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Yusof A, A. Mahmoud M, Ahmad MS. A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions. In 2nd International Symposium on Agent, Multi-Agent Systems and Robotics, ISAMSR 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 133-138. 7810016 https://doi.org/10.1109/ISAMSR.2016.7810016