Multi-Databases: Removal of Redundant Information

Abstract

This effort included the partial development of a search engines for multimedia web documents and the complete implementation of a prototype methodology for removing (partially or totally) redundant information from multiple documents in an effort to synthesize new documents. A typical multimedia document contains free text and images and additionally has associating well-structured data. An SQL-like query language, WebSSQL, has been used to retrieve these types of documents. The main differences between Web SSQL and other proposed SQL extensions for retrieving web documents are that Web SSQL is similarity-based and supports conditions on images. This report also describes a software methodology for the detection and removal of redundant information (text paragraphs and images) from multiple retrieved documents. Documents reporting the same or related events and stories may contain substantial redundant information. The removal of the redundant information and the synthesis of these documents into a single document can not only save a user's time to acquire the information, but also storage space to archive the data. The methodology reported here consists of techniques for analyzing text paragraphs and images as well as a set of similarity criteria used to detect redundant paragraphs and images. The methodology developed in this project has the ability either to work independently with text paragraphs and images, or to combine both in one synthetic document.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2000
Accession Number
ADA386557

Entities

People

  • Nicholas G. Bourbakis
  • Weiyi Meng

Organizations

  • Binghamton University

Tags

Communities of Interest

  • Biomedical
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • African Americans
  • Air Force
  • Air Force Research Laboratories
  • Computer Science
  • Databases
  • Detection
  • Education
  • Laboratory Procedures
  • Language
  • Military Research
  • Native Americans
  • Natural Languages
  • New England
  • New York
  • Periodicals
  • Prototypes
  • Relational Databases

Fields of Study

  • Computer science

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Database Systems and Applications
  • Library and Information Science

Technology Areas

  • Space
  • Space - Space Objects