A Kind of Improved Data Clustering Algorithm in Web Log Mining

DOI

10.2991/isrme-15.2015.438How to use a DOI?

Keywords

Web Log; Clustering; K-means; Fuzzy Matrix;

Abstract

Aiming at the user clustering and page clustering in Web log mining and based on the analysis of K-means clustering algorithm and matrix clustering algorithm, the paper presented an improved clustering algorithm that combining fuzzy matrix algorithm with K-means algorithm. Extract compressed sub-matrix from relational matrix of user and page, establishing user interval, and then divide all users into large intervals and separate the noise data, obtain initial value and classified number for K-means algorithm, effectively solve the defect in the K-means algorithm that always suppose or make a try to definite the classified number and the initial value, also include the lacking to exclude the noise data obstruction.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jin Guo
AU  - Shengbing Zhang
AU  - Zheng Qiu
PY  - 2015/04
DA  - 2015/04
TI  - A Kind of Improved Data Clustering Algorithm in Web Log Mining
BT  - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering
PB  - Atlantis Press
SP  - 2115
EP  - 2119
SN  - 1951-6851
UR  - https://doi.org/10.2991/isrme-15.2015.438
DO  - 10.2991/isrme-15.2015.438
ID  - Guo2015/04
ER  -