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Various users with different data needs must explore big data, which refers to large data repositories continually being added to the internet in the modern digital landscape. However, when looking for specific data, typical users frequently encounter difficulties such as lengthy search times and complex computational procedures, which can be uncomfortable and time-consuming. Additionally, obtaining the needed information from these vast data warehouses depends critically on the quality of the search results. This research aims to create an effective solution using an exact string-searching algorithm in response to the recognition of this frequent and constant requirement among regular users. Compared to other precise string searching methods, this algorithm's simplicity promises to increase effectiveness and cut down on processing time, especially in terms of complexity at its worst. A comparative analysis is conducted between the proposed algorithm and the Naive Approach, Boyer Moore Hoorspool, Knuth Morris Pratt (KMP), and Back and Forth Matching Algorithms to evaluate the method's performance fully.
Rehman et al. (Mon,) studied this question.