Advanced Search Technologies for Unfamiliar Metadata

Abstract

Searching of databases (textual or numeric) is likely to be effective and efficient only if the user is familiar with the classification, categorizing, and indexing schemes (metadata vocabularies) being searched. Therefore, it is obviously beneficial to provide a bridge between the user's ordinary language and the metadata vocabularies of the unfamiliar database to compensate for abbreviated, cryptic, or specialized terminologies. Advanced search technologies would utilize customized "Entry Vocabulary Modules" (EVM) that respond adaptively to the user's ordinary language query with a ranked list of search terms in the target metadata vocabularies that may more accurately represent what is sought in the unfamiliar database. These EVMs can serve both as an indexing device and a search aid. This project has developed EVMs for several metadata vocabularies, including domestic and international patent classifications and U.S. Standard Industrial Classification Codes. An agent-based architecture is under design to lighten the task of cracking alien metadata vocabularies.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2001
Accession Number
ADA455469

Entities

People

  • Aitao Chen
  • Barbara Norgard
  • Byron Lam
  • Fredric C. Gey
  • Hui-min Chen
  • Jacek Purat
  • Michael Buckland
  • Ray Larson
  • Youngin Kim

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Classification
  • Commerce
  • Computers
  • Databases
  • Dictionaries
  • Graphical User Interface
  • Information Retrieval
  • Information Science
  • Instructions
  • International Trade
  • Language
  • Metadata
  • Natural Languages
  • Public Administration
  • Standards
  • United States

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Linguistics