SEMANTIC NESTED SEARCH ENGINE VIA INTEGRATION ONTOLOGY WITH MULTI-AGENT SYSTEM
Elsayed, E., ELHabashy, A., khaled, R. (2019). SEMANTIC NESTED SEARCH ENGINE VIA INTEGRATION ONTOLOGY WITH MULTI-AGENT SYSTEM. EKB Journal Management System, 30(Issue 1-B), 27-36. doi: 10.21608/absb.2019.66075
Eman K. Elsayed; AbdAllah A. ELHabashy; Raghda M. khaled. "SEMANTIC NESTED SEARCH ENGINE VIA INTEGRATION ONTOLOGY WITH MULTI-AGENT SYSTEM". EKB Journal Management System, 30, Issue 1-B, 2019, 27-36. doi: 10.21608/absb.2019.66075
Elsayed, E., ELHabashy, A., khaled, R. (2019). 'SEMANTIC NESTED SEARCH ENGINE VIA INTEGRATION ONTOLOGY WITH MULTI-AGENT SYSTEM', EKB Journal Management System, 30(Issue 1-B), pp. 27-36. doi: 10.21608/absb.2019.66075
Elsayed, E., ELHabashy, A., khaled, R. SEMANTIC NESTED SEARCH ENGINE VIA INTEGRATION ONTOLOGY WITH MULTI-AGENT SYSTEM. EKB Journal Management System, 2019; 30(Issue 1-B): 27-36. doi: 10.21608/absb.2019.66075

SEMANTIC NESTED SEARCH ENGINE VIA INTEGRATION ONTOLOGY WITH MULTI-AGENT SYSTEM

Al-Azhar Bulletin of Science
Article 3, Volume 30, Issue 1-B, June 2019, Page 27-36  XML PDF (746.4 K)
Document Type: Original Article
DOI: 10.21608/absb.2019.66075
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Authors
Eman K. Elsayed email orcid 1; AbdAllah A. ELHabashyorcid 2; Raghda M. khaled3
1Department of mathematics and Computer Science, Faculty of science, Al-Azhar University (Girls),Cairo, Egypt
2Department of mathematics and Computer Science, Faculty of science, Alazhar University, Cairo, Egypt.
3Department of mathematics and Computer Science, Faculty of science, Al-Azhar University (Girls),Cairo, Egypt
Abstract
Global and private search engines retrieve a huge amount of information within thousands of web pages. That is based on user’s search criteria. Nevertheless, it is a challenge to analyze all the information retrieved to match her/his required information. Solving this challenge needs to combine information retrieval systems (IR) with text mining and artificial intelligent approaches. This paper proposes enhanced search engines to be semantic nested search which can be used in business domain. This is via integrating Ontology, Multi-agent technology, and human computer interaction (HCI) concepts. Where Ontology provides a semantic view for understanding the pages contents then Multi-agent collects synchronously the selected information from each link. The proposed semantic nested search engine (SNS) have three phases and use four agents. The SNS engine will be applied on three case studies; jobs search, ecommerce products search and the scientific conferences search. We use different accuracy measurement such as relevant results, recall, precision and F-score. Also, we compare the proposed SNS engine with Google, Yahoo and Bing general search engines. The proposed system consume time. But the run time is not bad relative to the manual searching time inside the links, i.e. overall, the proposed SNS saves users’ time and effort.
Keywords
Multi-Agent; ontology; Human Computer Interaction (HCI); Information Retrieve (IR)
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