Name
Title | ||
|---|---|---|
Spectral Clustering of Customer Transaction Data With a Two-Level Subspace Weighting Method |
Abstract | ||
|---|---|---|
Finding customer groups from transaction data is very important for retail and e-commerce companies. Recently, a ``Purchase Tree'' data structure is proposed to compress the customer transaction data and a local PurTree spectral clustering method is proposed to cluster the customer transaction data. However, in the PurTree distance, the node weights for the children nodes of a parent node are set as equal and the differences between different nodes are not distinguished. In this paper, we propose a two-level subspace weighting spectral clustering (TSW) algorithm for customer transaction data. In the new method, a PurTree subspace metric is proposed to measure the dissimilarity between two customers represented by two purchase trees, in which a set of level weights are introduced to distinguish the importance of different tree levels and a set of sparse node weights are introduced to distinguish the importance of different tree nodes in a purchase tree. TSW learns an adaptive similarity matrix from the local distances in order to better uncover the cluster structure buried in the customer transaction data. Simultaneously, it learns a set of level weights and a set of sparse node weights in the PurTree subspace distance. An iterative optimization algorithm is proposed to optimize the proposed model. We also present an efficient method to compute a regularization parameter in TSW. TSW was compared with six clustering algorithms on ten benchmark data sets and the experimental results show the superiority of the new method. IEEE |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TCYB.2018.2836804 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Clustering,Clustering algorithms,clustering tree,Companies,customer segmentation,Cybernetics,Measurement,Sparse matrices,Sun,two level weighting,Vegetation | Data structure,Data mining,Spectral clustering,Data set,Weighting,Subspace topology,Artificial intelligence,Cluster analysis,Transaction data,Machine learning,Sparse matrix,Mathematics | Journal |
Volume | Issue | ISSN |
49 | 9 | 21682267 |
Citations | PageRank | References |
8 | 0.43 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaojun Chen | 1 | 1298 | 107.51 |
| Wenya Sun | 2 | 8 | 0.76 |
| Bo Wang | 3 | 224 | 53.43 |
| Zhihui Li | 4 | 252 | 16.39 |
| Xizhao Wang | 5 | 3593 | 166.16 |
| Ye Yunming | 6 | 440 | 39.77 |