Toward a Unified Retrieval Outcome Analysis Framework for Cross-Language Information Retrieval Metadata

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Title

  • Main Title Toward a Unified Retrieval Outcome Analysis Framework for Cross-Language Information Retrieval

Creator

  • Author: Chen, Jiangping
    Creator Type: Personal
    Creator Info: University of North Texas

Contributor

  • Organizer of meeting: American Society for Information Science and Technology
    Contributor Type: Organization

Date

  • Creation: 2005

Language

  • English

Description

  • Content Description: This paper proposes a Retrieval Outcome Analysis Framework, or ROA Framework, to systematically evaluate retrieval performance of Cross-Language Information Retrieval systems.
  • Physical Description: 11 p.

Subject

  • Keyword: cross-language searches
  • Keyword: search and retrieval systems
  • Keyword: online language translators
  • Keyword: retrieval performance evaluation

Source

  • Conference: Sixty-Eighth Annual Meeting of the American Society for Information Science and Technology (ASIS&T), 2005, Charlotte, North Carolina, United States

Collection

  • Name: UNT Scholarly Works
    Code: UNTSW

Institution

  • Name: UNT College of Information
    Code: UNTCOI

Rights

  • Rights Access: public

Resource Type

  • Paper

Format

  • Text

Identifier

  • Archival Resource Key: ark:/67531/metadc132969

Degree

  • Academic Department: Library and Information Science

Note

  • Display Note: Abstract: This paper proposes a Retrieval Outcome Analysis Framework, or ROA Framework, to systematically evaluate retrieval performance of Cross-Language Information Retrieval systems. The ROA framework goes beyond TREC-type retrieval evaluation methodology by including procedures focusing on individual queries, especially difficult queries. The framework is comprised of four interrelated components: (1) Overall System Performance Evaluation, (2) Query Categorization, (3) Translation Analysis, and (4) Individual Query Analysis. An example of applying the framework is discussed in detail. The author believes the proposed framework would be especially useful for the development of real world Cross-Language Information Retrieval systems because the evaluation guided by the framework has the potential to discover causes behind poor retrieval performance.