System and method for sequence-based subspace pattern clustering
US7565346B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 31, 2004 |
| Grant date | Jul 21, 2009 |
| Priority date | — |
| Expiry date | Apr 19, 2025 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/22
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Unlike traditional clustering methods that focus on grouping objects with similar values on a set of dimensions, clustering by pattern similarity finds objects that exhibit a coherent pattern of rise and fall in subspaces. Pattern-based clustering extends the concept of traditional clustering and benefits a wide range of applications, including e-Commerce target marketing, bioinformatics (large scale scientific data analysis), and automatic computing (web usage analysis), etc. However, state-of-the-art pattern-based clustering methods (e.g., the pCluster algorithm) can only handle datasets of thousands of records, which makes them inappropriate for many real-life applications. Furthermore, besides the huge data volume, many data sets are also characterized by their sequentiality, for instance, customer purchase records and network event logs are usually modeled as data sequences. Hence, it becomes important to enable pattern-based clustering methods i) to handle large datasets, and ii) to discover pattern similarity embedded in data sequences. There is presented herein a novel method that offers this capability.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.