A Probabilistic Approach to Crosslingual Information Retrieval

Abstract

We present a method to translate queries from an arbitrary source language to retrieve documents in a destination language merely with easily obtainable instruments such as a machine readable dictionary and monolingual corpora in both languages. The key is to infer probabilistical information about the query and structuring the destination language terms accordingly. Though the results compare unfavourably with those obtained with more sophisticated but difficult to obtain IR-methods using Part-of-Speech-Tagging and/or Phrase dictionaries, our work shows the successful deployment and combination of related work to crosslingual Information Retrieval.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2001
Accession Number
ADA477981

Entities

People

  • Philip Groeting

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Agreements
  • Algorithms
  • Automated Speech Recognition
  • Channel Models
  • Computational Complexity
  • Computational Processes
  • Databases
  • Deployment
  • Dictionaries
  • Information Retrieval
  • Language
  • Precision
  • Probability
  • Second World War
  • Translations
  • War
  • Words (Language)

Fields of Study

  • Computer science

Readers

  • Computational Linguistics

Technology Areas

  • AI & ML
  • AI & ML - Information Retrieval
  • AI & ML - Machine Translation