An Algorithm for Optimized Searching using NON-Overlapping Iterative Neighbor intervals

TL;DR

This paper introduces a novel optimized search algorithm that enhances the plane sweep method by using non-overlapping neighbor intervals to efficiently identify minimal keyword groups in large datasets.

Contribution

The paper proposes a new approach that reduces comparisons and improves efficiency in keyword search by focusing on non-overlapping intervals near minimum frequency keywords.

Findings

Reduces number of comparisons in search process

Increases efficiency and reliability over previous methods

Effective in high-volume data environments

Abstract

We have attempted in this paper to reduce the number of checked condition through saving frequency of the tandem replicated words, and also using non-overlapping iterative neighbor intervals on plane sweep algorithm. The essential idea of non-overlapping iterative neighbor search in a document lies in focusing the search not on the full space of solutions but on a smaller subspace considering non-overlapping intervals defined by the solutions. Subspace is defined by the range near the specified minimum keyword. We repeatedly pick a range up and flip the unsatisfied keywords, so the relevant ranges are detected. The proposed method tries to improve the plane sweep algorithm by efficiently calculating the minimal group of words and enumerating intervals in a document which contain the minimum frequency keyword. It decreases the number of comparison and creates the best state of optimized search algorithm especially in a high volume of data. Efficiency and reliability are also increased compared to the previous modes of the technical approach.