Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{173184,
        author = {Prof.Rajendra Parshram Sabale and Prof.Prakash Chhagan Patil and Prof.Somnath B.Lavhate and Prof. Rajendra  Belkar},
        title = {Intergation of  Fuzzy Logic and Machine Learning Techniques for improving  accuracy and efficiency of  searching systems.},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {9},
        pages = {2358-2360},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=173184},
        abstract = {The exponential growth of digital data has necessitated the development of intelligent search systems. This paper proposes a novel approach that integrates fuzzy logic and machine learning techniques to enhance the accuracy and efficiency of search results. The proposed system utilizes fuzzy logic to model user queries and document relevance, while machine learning algorithms are employed to learn patterns in user behavior and improve search accuracy. Experimental results demonstrate the effectiveness of the proposed approach in improving the precision and recall of search results.},
        keywords = {Fuzzy logic, machine learning, intelligent search systems, information retrieval, natural language processing, text categorization.},
        month = {February},
        }