KOJAK Group Finder: Scalable Group Detection via Integrated Knowledge-Based and Statistical Reasoning

Abstract

This report describes the KOJAK Group Finder which is a highly scalable, hybrid logic-based statistical link discovery system designed to solve group detection problems. The system takes primary and secondary evidence as input and produces group hypotheses with ranked lists of group members as output. Under funding of this project, the Group Finder was developed from a research prototype into a mature software component that can be transitioned into operational environments. Among the many improvements, scalability and processing speed was improved by over a factor of 10, the software is now available in C++ and Java versions for Linux, as well as Windows platforms and now also supports Oracle databases in addition to MySQL. A Java-based GUI was added to facilitate usage by non-experts.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2006
Accession Number
ADA457191

Entities

People

  • Hans Chalupsky
  • Jafar Adibi
  • Thomas A. Russ

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Computer Program Reliability
  • Computer Programming
  • Computer Programs
  • Computers
  • Database Management Systems
  • Databases
  • Department Of Defense
  • Detection
  • Graphical User Interface
  • Information Science
  • Lisp Programming Language
  • Metal Matrix Composites
  • Operating Systems
  • Reasoning
  • Relational Database Management Systems
  • Relational Databases
  • Reliability

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Database Systems and Applications
  • Systems Analysis and Design