SKIPAL: The Incorporation of Machine Learning Technology into the Strategic Knowledge Integration Web
Abstract
The Personalized Assistant that Learns (PAL) program was a DARPA research program with the primary goal of creating an integrated system that can adapt to changes in its environment and the users' goals and tasks without programming assistance or technical intervention. SKIWeb is an information aggregation system based at USSTRATCOM and is available to anyone on SIPRNET, a secure internet for the US Department of Defense. With a user base over twenty five thousand, and a constantly growing number of human and automated contributors, SKIWeb content threatens to overwhelm users, causing them to miss critical information amid a deluge of information. We hypothesized that PAL technology could be used to learn the information the user requires by observing the implicit and explicit signals in their interaction with SKIWeb; and that further, PAL technology could help with event identification and to expose the relationships between events and SKIWeb users, both of which could be leveraged to improve efficiency and quality in USSTRATCOM operations. Based on experimental results USSTRATCOM has made the required budget requests to transition SKIPAL to a program of record. This paper describes the technologies incorporated into SKIPAL, results of the experimentation, and methods that have led to both a technical and programmatic transition success.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2010
- Accession Number
- ADA525234
Entities
People
- Andrew S. Ling
- Bill Deans
- Bill Graves
- Douglas S. Lange
- Edward C. Lai
- John Bolton
- Kellie Keifer
- Ken Nitz
- Laura Tam
- Michael Carlin
Organizations
- Naval Information Warfare Systems Command