Chance Discovery with Data Crystallization: A Basic Research for Discovering Unobservable Events

Abstract

It is only the observable part of the real world that can be presented in data. For such a scattered, i.e., an incomplete and ill-structured data, data crystallizing aims at presenting the hidden structure by inserting dummy items corresponding to unobservable, i.e., hidden events, to the given data on past events. The existence of hidden events and their position in the environment will be visualized as a result of data crystallizing. This basic method is expected to be applicable for various real world domains to which chance-discovery methods have been applied. This project aims at developing the process of data crystallizing, with a new tool extending KeyGraph, based on the process of chance discovery. In the research, experiments will be made using artificial data obtained from simulating the target of intelligence analysis, i.e., organized crimes.

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Document Details

Document Type
Technical Report
Publication Date
May 10, 2006
Accession Number
ADA456092

Entities

People

  • Yukio Ohsawa

Organizations

  • University of Tsukuba

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Commerce
  • Computational Science
  • Computations
  • Computers
  • Data Mining
  • Data Visualization
  • Electronic Mail
  • Information Science
  • Machine Learning
  • Materials Science
  • Network Science
  • Personnel Management
  • Self Organizing Systems
  • Statistical Analysis
  • Teamwork

Fields of Study

  • Chemistry

Readers

  • Aerospace Engineering
  • Materials Science and Engineering.
  • Systems Analysis and Design