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/).
Cite this article
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 -