Name
Abstract | ||
|---|---|---|
SRI's LAW (Link Analysis Workbench) is a system that helps intelligence analysts detect occurrences of situations of interest by finding pattern instances in vast amounts of data using graph edit distance matching techniques. However to be completely successful it has to convey the results of the such findings to the users in a way that they can quickly grasp, not only to make use of it or to present it, but also to provide the feedback necessary to fine tune the discovery process using LAW. This paper presents what we think is required in order to achieve this goal, the solutions that were designed and implemented in the current LAW architecture and the approach that we envision in the next installments of LAW . |
Year | Venue | Field |
|---|---|---|
2006 | AAAI Fall Symposium: Capturing and Using Patterns for Evidence Detection | Computer science,Link analysis,Artificial intelligence,Machine learning |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
1 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jerome Thomere | 1 | 1 | 1.04 |
| Michael Wolverton | 2 | 264 | 28.16 |