Adaptively Intelligent Meta-search Engine with Minimum Edit Distance

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dc.contributor.authorKanwal, Asma
dc.contributor.authorSeptyanto, Arif Wicaksono
dc.contributor.authorMuhammad, Muhammad Hassan Ghulam
dc.contributor.authorSaid, Raed A.
dc.contributor.authorFarrukh, Muhammad
dc.contributor.authorIbrahim, Muhammad
dc.date.accessioned2022-05-22T10:27:03Z
dc.date.available2022-05-22T10:27:03Z
dc.date.copyright© 2022
dc.date.issued2022
dc.descriptionThis conference paper is not available at CUD collection. The version of scholarly record of this paper is published in 2022 International Conference on Business Analytics for Technology and Security (ICBATS) (2022), available online at: https://doi.org/10.1109/ICBATS54253.2022.9759088
dc.description.abstractIn current era retrieval of information has attained high demand due to spectra from websites has abundantly increased. Search Engines are basic tools to get information from the web of data and show irrelevant data causing wastage of time. Considering the fact that time is a precious commodity and is the hallmark of everything around us. To overcome the wastage of time and for its optimum utilization meta-search engines are design. Meta-Search Engine use to fetch relevant data. Existing meta-search engine shows their relevant data based on keywords as well as a semantic query. Semantic query-based results still have some irrelevancy in the results. In this paper, we analyze the semantic query based on machine learning algorithms. This paper hypothesizes improved results through the query expansion mechanism. Author also remove duplicated URLs that come from multiple search engines. Minimum Edit Distance algorithm is used to measure the similarity between titles, snippets and if measuring similarity is more than 0.6 then it must remove that title and snippet. Ranking process, generated retrieval of the relevant document at the top relevant document. Comparative analysis of proposed work is done with existing meta-search engines, overall performance of Intelligent Meta-Search Engine (IMSE) remains 74.17%. © 2022 IEEE.
dc.identifier.citationKanwal, A., Septyanto, A. W., Muhammad, M. H. G., Said, R. A., Farrukh, M., & Ibrahim, M. (2022). Adaptively intelligent meta-search engine with minimum edit distance. 2022 International Conference on Business Analytics for Technology and Security (ICBATS). https://doi.org/10.1109/ICBATS54253.2022.9759088
dc.identifier.isbn978-166540920-9
dc.identifier.urihttps://doi.org/10.1109/ICBATS54253.2022.9759088
dc.identifier.urihttp://hdl.handle.net/20.500.12519/653
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relationAuthors Affiliation : Kanwal, A., Gcu, Department of Computer Science, Lahore, Pakistan; Septyanto, A.W., Bangsa University Surakarta, Department Information System, Surakarta, Indonesia; Muhammad, M.H.G., NCBAandE, School of Computer Science, Lahore, Pakistan; Said, R.A., Canadian University, Dubai, United Arab Emirates; Farrukh, M., Gcu, Department of Computer Science, Lahore, Pakistan; Ibrahim, M., NCBAandE, School of Computer Science, Lahore, Pakistan
dc.relation.ispartofseries2022 International Conference on Business Analytics for Technology and Security (ICBATS)
dc.rightsPermission to reuse abstract has been secured from Institute of Electrical and Electronics Engineers Inc.
dc.rights.holderCopyright : © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.rights.urihttps://www.ieee.org/publications/rights/rights-policies.html
dc.subjectIMSE
dc.subjectMeta-Search Engine
dc.subjectNamed Entity Recognizer
dc.subjectNatural Language Processing
dc.subjectStemming
dc.titleAdaptively Intelligent Meta-search Engine with Minimum Edit Distance
dc.typeConference Paper
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