Method for Measuring the Semantic-similarity of Textual Document and Web-pages
Jasurbek Atadjanov1, Boburbek Atadjanov2, Shakhboz Abdulazizov3, Orif Makhmanov4
1Jasurbek Atadjanov*, Software Developer at Uztelecom, Tashkent University of Information Technologies (TUIT), Tashkent, Uzbekistan.
2Bobur Atadjanov, Software Developer at Uztelecom, Tashkent University of Information Technologies (TUIT), Tashkent, Uzbekistan.
3Shakhboz Abdulazizov, Software Developer at Uztelecom Stock Company, Bachelor of Science in Computer Science and Software Engineering from Inha University in Tashkent (IUT).
4Orif Makhmanov, Deputy Director at the Center of Introduction and Development of Information and Communication Technologies, Tashkent, Uzbekistan.
Manuscript received on November 15, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 1601-1606 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7314129219/2019©BEIESP | DOI: 10.35940/ijitee.B7314.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this article, the process of semantic comparison of web pages in the global network is addressed. Comparing process is done based on set of words in text. Google Ajax Search and Yandex-API services are used to search and find web pages in global network. The local database is used for the determination of synonyms of the words. For the experiment, we took a document from Global network and its text was exchanged to synonyms and generated new document. The generated document compared with the given algorithm and it showed 90-95% similarity. The developed system with this algorithm used in Tashkent University of Information Technologies named after Muhammad Al-Khwarizmi for verifying students Graduation Qualification works for plagiarism.
Keywords: Stemming Text, Search Information from Document, Semantic Analyze Documents.
Scope of the Article: Community Information Systems