Semantic Based Intelligent Information Retrieval through Data mining and Ontology

Ahmed, Muqeem; It, Manuu

doi:10.26438/ijcse/v5i10.210217

Cited by 2 publications

(2 citation statements)

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“…It expands the category words semantics structure and then retrieves the information to the user interface. According to Ahmed (2017), finding specific concept matching is easy, and the challenging part is to match unsettled related concepts using knowledge repository. It provides concepts' details and their connections with other concepts and involves two steps: tokenizing user query and extracting vital domain words from tokenized terms (Ahmed, 2017).…”

Section: Semantic Analysismentioning

confidence: 99%

“…According to Ahmed (2017), finding specific concept matching is easy, and the challenging part is to match unsettled related concepts using knowledge repository. It provides concepts' details and their connections with other concepts and involves two steps: tokenizing user query and extracting vital domain words from tokenized terms (Ahmed, 2017). Irrelevant concepts are removed, and suitable ones are linked to documents for query creation.…”

Section: Semantic Analysismentioning

confidence: 99%

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Intelligent Information Retrieval System

Abimbola¹

2022

International Journal of Artificial Intelligence and Machine Learning

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An Intelligent Information Retrieval (IIR) is a machine learning system used by users to retrieve the massive volume of information available through internet. IIR offers personalization and efficiency in the current internet development allowing users to examine and acquire appropriate information. The paper will focus on the keyword searching issues of the current digital library system. The paper will analyze a model that solves the issue using metadata case-based and concept-based approach. The objective is to evaluate a set of categories and concepts in the domain field that demonstrates some relations between them to elaborate how poor quality of information retrieval in digital library system can be solved. The paper further argued that the already developed domain-specific ontology can be efficient for query advancement. Many researchers have used semantic retrieval technology using concepts to solve problems that lack semantics in traditional retrieval technology. Using concepts in ontology enhances search results

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Section: Semantic Analysismentioning

confidence: 99%

Section: Semantic Analysismentioning

confidence: 99%