IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 14, No 3: June 2025

Evaluating search key distribution impact on searching performance in large data streams

Srisungsittisunti, Bowonsak (Unknown)
Duangkaew, Jirawat (Unknown)
Chaikaew, Nakarin (Unknown)



Article Info

Publish Date
01 Jun 2025

Abstract

The distribution pattern of search keys is assessed in this study by contrasting four methods of index searching on large-scale JSON files with data streams. The Adelson-Velskii and Landis (AVL) tree, binary search tree (BST), linear search (LS), and binary search (BS) are among the search strategies. We look at the normal distribution, left-skewed distribution, and right-skewed distribution of search-key distributions. According to the results, LS performs the slowest, averaging 653.166 milliseconds, whereas AVL tree performs better than the others in dense index, with an average search time of 0.005 milliseconds. With 0.011 milliseconds per keyword for sparse index, BS outperforms LS, which averages 1007.848 milliseconds. For dense indexing, an AVL tree works best; for sparse indexing, BS is recommended.

Copyrights © 2025






Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...