Open AccessA Feature Clustering-Based IP Localization Algorithm
Author(s) -
Yong Gan,
Yifan Wang,
Dongwei Jia
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2025/1/012034
Subject(s) - computer science , cluster analysis , data mining , classifier (uml) , reliability (semiconductor) , feature (linguistics) , artificial intelligence , machine learning , power (physics) , linguistics , physics , philosophy , quantum mechanics
The geographic location of network IP is an important foundation of location-based services, which plays an increasingly important role in people’s daily life and work. However, the existing IP location methods based on database query, network measurement and machine learning often have some problems, such as poor timeliness, low reliability, difficult feature modeling and so on, or need a large amount of user data as support, which is often only suitable for the more ideal network environment, so the positioning accuracy and applicability are far from the actual needs. To solve this problem, this paper proposes an IP location method based on clustering. The initial IP address of the classifier is located by training. Combined with the method of IP address database matching, the accurate location of IP address is finally realized. Experimental results show the effectiveness of the method.