An ontopark ranking framework for semantic web mining

Ontology is used for ranking the webpages using the semantic recommendation system. Ontology matching with the semantics of words in the said query makes the use of the web and identifies the semantic ontologies by differentiating relevant and irrelevant ontologies. The filtered results from the merging of ontologies are processed to semantic recommendation modules to calculate similarity, pattern analysis and probabilistic ranking of webpages. Semantics discovers ontologies from the domain. The use and merging of ontologies with relations provide high interpretability of recommendations. After merging ontologies, the results are forwarded to the recommendation phase. The semantic recommended results are computed on the categories such as books, online web pagination, projects, repositories, experts of the subject, citations and online journals. Semantic recommendation system allows a number of users to create their login area and construct a logfile to store previous searched queries by the individual then display the recommended results on the basis of previous queries. Thus, Ontopark Ranking Framework for Semantic Web Mining is the optimizing technique to detect online user behavior.

• Publication year

  2025

• Venue

  E-Learning and Digital Media

• Publication date

  2025-09-01

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1177/20427530241282252
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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