Academic Journal
Optimal Web Page Retrieval Using Evolutionary Genetic Algorithm.
| Τίτλος: | Optimal Web Page Retrieval Using Evolutionary Genetic Algorithm. |
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| Συγγραφείς: | Katke, Snehal Mahesh |
| Πηγή: | International Scientific Journal of Engineering & Management; Jun2026, Vol. 5 Issue 6, p1-5, 5p |
| Θεματικοί όροι: | Genetic algorithms, Internet searching, Java programming language, Search engines, Information retrieval, Intelligent agents |
| Περίληψη: | The rapid expansion of digital content on the World Wide Web has made efficient information retrieval an increasingly complex challenge. To assist users in navigating this vast information landscape, several retrieval mechanisms have been developed. Among these, two broad strategies are commonly employed: structured index-based search and autonomous agent-driven search. This work presents an intelligent search agent that leverages a Genetic Algorithm (GA) to perform global web searches. The agent is implemented using the Java programming language and operates by evaluating multiple candidate documents to identify the most relevant result for a given input. The proposed system is built on the Java platform and integrates the Merriam-Webster lexical database to expand query terms with their semantic equivalents. Query words are tokenized, synonym tables are constructed, and varied term combinations are assembled and dispatched to a search engine parser. The returned web pages represent the most semantically aligned results for the original query. [ABSTRACT FROM AUTHOR] |
| Copyright of International Scientific Journal of Engineering & Management is the property of International Scientific Journal of Engineering & Management and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Text: Availability: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Optimal Web Page Retrieval Using Evolutionary Genetic Algorithm. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Katke%2C+Snehal+Mahesh%22">Katke, Snehal Mahesh</searchLink> – Name: TitleSource Label: Source Group: Src Data: International Scientific Journal of Engineering & Management; Jun2026, Vol. 5 Issue 6, p1-5, 5p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+searching%22">Internet searching</searchLink><br /><searchLink fieldCode="DE" term="%22Java+programming+language%22">Java programming language</searchLink><br /><searchLink fieldCode="DE" term="%22Search+engines%22">Search engines</searchLink><br /><searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22Intelligent+agents%22">Intelligent agents</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The rapid expansion of digital content on the World Wide Web has made efficient information retrieval an increasingly complex challenge. To assist users in navigating this vast information landscape, several retrieval mechanisms have been developed. Among these, two broad strategies are commonly employed: structured index-based search and autonomous agent-driven search. This work presents an intelligent search agent that leverages a Genetic Algorithm (GA) to perform global web searches. The agent is implemented using the Java programming language and operates by evaluating multiple candidate documents to identify the most relevant result for a given input. The proposed system is built on the Java platform and integrates the Merriam-Webster lexical database to expand query terms with their semantic equivalents. Query words are tokenized, synonym tables are constructed, and varied term combinations are assembled and dispatched to a search engine parser. The returned web pages represent the most semantically aligned results for the original query. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of International Scientific Journal of Engineering & Management is the property of International Scientific Journal of Engineering & Management and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edb&AN=195396405 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.55041/ISJEM07804 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 5 StartPage: 1 Subjects: – SubjectFull: Genetic algorithms Type: general – SubjectFull: Internet searching Type: general – SubjectFull: Java programming language Type: general – SubjectFull: Search engines Type: general – SubjectFull: Information retrieval Type: general – SubjectFull: Intelligent agents Type: general Titles: – TitleFull: Optimal Web Page Retrieval Using Evolutionary Genetic Algorithm. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Katke, Snehal Mahesh IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 25836129 Numbering: – Type: volume Value: 5 – Type: issue Value: 6 Titles: – TitleFull: International Scientific Journal of Engineering & Management Type: main |
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