Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Madrakhimov, Shavkat
Unknown Affiliation
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Choosing allowability boundaries for describing objects in subject areas Lolaev, Musulmon; Madrakhimov, Shavkat; Makharov, Kodirbek; Saidov, Doniyor
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i1.pp329-336

Abstract

Anomaly detection is one of the most promising problems for study and can be used as independent units and preprocessing tools before solving any fundamental data mining problems. This article proposes a method for detecting specific errors with the involvement of experts from subject areas to fill knowledge. The proposed method about outliers hypothesizes that they locate closer to logical boundaries of intervals derived from pair features, and the interval ranges vary in different domains. We construct intervals leveraging pair feature values. While forming knowledge in a specific field, a domain specialist checks the logical allowability of objects based on the range of the intervals. If the objects are logical outliers, the specialist ignores or corrects them. We offer the general algorithm for the formation of the database based on the proposed method in the form of a pseudo-code, and we provide comparison results with existing methods.
Co-Authors Lolaev, Musulmon Makharov, Kodirbek Saidov, Doniyor