Systems and methods for clustering user sessions using multi-modal information including proximal cue information
US7043475B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 19, 2002 |
| Grant date | May 9, 2006 |
| Priority date | — |
| Expiry date | Aug 3, 2024 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY10S707/99936
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques for clustering user sessions using multi-modal information including proximal cue information are provided. The topology, content and usage of a document collection or web site are determined. User paths are then identified using longest repeating subsequence techniques. An information need feature vector is determined for each significant user path. Further, other feature vectors and proximal cue vectors for each document or web page in the significant path are determined. The other feature vectors include a content feature vector, a uniform resource locator feature vector, an inlink feature vector and an outlink feature vector, among others. The feature vectors and the proximal cue vectors are combined into a multi-modal vector that represents a user profile for each significant user path. The multi-modal vectors are clustered using a type of multi-modal clustering such as K-Means or Wavefront clustering.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.