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Research Article

Enhancing Search Precision Through Dictionary Lexical Analysis

Open Access Peer Reviewed

Authors

  • A. Joyal Jones1
  • Dr. V. Vaidehi2

PG Student, Department of Computer Applications, DR MGR Educational and Research institute Chennai, Tamil Nadu, India. 2 Professor, Department of Computer Applications, DR MGR Educational and Research institute Chennai, Tamil Nadu, India

Article Information

DOI
No DOI
Published Online
May-June 2024
Pages
43-46
Article Type
Research Article
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No DOI available for cross-reference

Abstract

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Efficient and accurate search precision is crucial in information retrieval systems, especially as the volume of digital content continues to expand exponentially. This paper introduces a novel approach, "Enhancing Search Precision through Dictionary Lexical Analysis," designed to improve the precision of search queries by leveraging advanced lexical analysis techniques. The proposed system incorporates dictionary-based lexical analysis to enhance the understanding of user queries and refine search results. By mapping words to a comprehensive dictionary, the system identifies synonyms, acronyms, and related terms, creating an enriched semantic representation of the query. This process aids in capturing the nuanced context and intent behind user search queries, leading to more accurate and context-aware search results. Key components of the system include the construction and maintenance of a dynamic dictionary, lexical analysis algorithms, and integration with existing search engines. The dictionary is continuously updated to adapt to evolving language patterns and user preferences, ensuring the system remains effective over time. Through practical demonstrations and performance evaluations, this research showcases the impact of "Enhancing Search Precision through Dictionary Lexical Analysis" on search result relevance and user satisfaction. Comparative analyses against traditional search algorithms highlight the system's ability to provide more contextually relevant results, especially in ambiguous or specialized query contexts

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  • ISSN 2583-1240
  • Open Access
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