Available Methods in Farsi-English Cross Language Information Retrieval Using Machine-readable, Bilingual Glossary

Clicks: 415
ID: 82589
2009
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Star

Ranked #1 of 4 articles by views in iranian journal of information processing & management

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
In this paper the impact scope of Natural Language Processing (NLP) on translating search statements was determined by testing out research hypotheses. The NLP techniques employed for search statement processing included text parsing, linguistic forms identification, stopword removal, morphological analysis, and tokenization. Examination of the hypotheses indicated that using the method of translating the first equivalent term selected versus the method of selecting all equivalent terms, would contribute to increased efficiency of the review that while morphological analysis of the terms not translated by the glossary, would increase the retrieval precision cutoff, there would be no significant difference established by the lack of such analysis thereof that sentence translation as opposed to term by term translation, would increase the efficiency of Farsi-English proofreading. Other findings are also represented.
Reference Key
alizadeh2009availableiranian Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Alizadeh, Hamid;Fattahi, Rahmatullah;panah, Mohammad Reza Davar;
Journal iranian journal of information processing & management
Year 2009
DOI
DOI not found
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.