K-means Text Dynamic Clustering Algorithm Based on KL Divergence

• Published in: 2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) pp. 659 - 663
• Main Authors: Huan, Zhu, Pengzhou, Zhang, Zeyang, Gao
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2018
• Subjects: Clustering algorithms; Convergence; Entropy; Euclidean distance; Heuristic algorithms; K-means clustering algorithm; KL divergence; Probability distribution; text dynamic clustering; text similarity; text vectorization

The random selection of the initial cluster center and distance measure function selection in the classical k-means algorithm have a great influence on the time and final precision of the clustering. Based on the above two problems, this paper proposes the classical VSM (vector space model) to repre...