A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions
Commerce; Intelligent agents; Marketing; Robotics; Sales; Semantic Web; Social networking (online); Societies and institutions; Web Design; Websites; Conceptual model; Dynamic website; Generator systems; Grouping process; Rendering engine; Semantic web models; Semantics web; Strategic marketing; Mul...
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-233382023-05-29T14:39:37Z A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions Yusof A. Mahmoud M.A. Ahmad M.S. 35185858900 55247787300 56036880900 Commerce; Intelligent agents; Marketing; Robotics; Sales; Semantic Web; Social networking (online); Societies and institutions; Web Design; Websites; Conceptual model; Dynamic website; Generator systems; Grouping process; Rendering engine; Semantic web models; Semantics web; Strategic marketing; Multi agent systems 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. � 2016 IEEE. Final 2023-05-29T06:39:37Z 2023-05-29T06:39:37Z 2017 Conference Paper 10.1109/ISAMSR.2016.7810016 2-s2.0-85015005901 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015005901&doi=10.1109%2fISAMSR.2016.7810016&partnerID=40&md5=03dd5add9f833a38f734ec6e29fcfd9f https://irepository.uniten.edu.my/handle/123456789/23338 7810016 133 138 Institute of Electrical and Electronics Engineers Inc. Scopus |
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Commerce; Intelligent agents; Marketing; Robotics; Sales; Semantic Web; Social networking (online); Societies and institutions; Web Design; Websites; Conceptual model; Dynamic website; Generator systems; Grouping process; Rendering engine; Semantic web models; Semantics web; Strategic marketing; Multi agent systems |
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35185858900 |
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35185858900 Yusof A. Mahmoud M.A. Ahmad M.S. |
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Conference Paper |
author |
Yusof A. Mahmoud M.A. Ahmad M.S. |
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Yusof A. Mahmoud M.A. Ahmad M.S. A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions |
author_sort |
Yusof A. |
title |
A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions |
title_short |
A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions |
title_full |
A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions |
title_fullStr |
A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions |
title_full_unstemmed |
A Conceptual Multi-Agent Semantic Web Model of a self-Adaptive website for intelligent strategic marketing in learning institutions |
title_sort |
conceptual multi-agent semantic web model of a self-adaptive website for intelligent strategic marketing in learning institutions |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2023 |
_version_ |
1806428290734358528 |
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13.214268 |