Volume 32, Issue 4 (summer 2017)                   ... 2017, 32(4): 1143-1170 | Back to browse issues page

XML Persian Abstract Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Hosseini Beheshti M S, Abdi Ghavidel H. Categorization of Various Essential Datasets and Methods for Textual Spelling Detection and Normalization. .... 2017; 32 (4) :1143-1170
URL: http://jipm.irandoc.ac.ir/article-1-3088-en.html
Iranian Research Institute for Information Science and Technology(IranDoc)
Abstract:   (5938 Views)
One of the most primary phases of automatic text processing is spelling error detection and grapheme normalization. Storing textual documents faces several problems without passing this phase, which causes a disturbance in retrieving the documents automatically. Therefore, specialists in the fields of natural language processing and computational linguistics usually make an attempt to sample various data through presenting ideal methods and algorithms in order to reach the normalized data. Several researches have been conducted on English and some other languages, which have been followed by a certain amount of researches on Farsi too. Sometimes, these several researches have remained to be a pure study and sometimes they have been released as a product. This paper carries out the categorization of the different methods and essential datasets in these researches and depicts each category individually and the evaluation measurements methods generally. Moreover, it describes the performance of the monolingual Farsi systems and the way they meet the Farsi challenges.
Full-Text [PDF 812 kb]   (2315 Downloads)    
Type of Study: Review | Subject: Information Technology
Received: 2016/01/26 | Accepted: 2016/08/2 | Published: 2016/08/21

Add your comments about this article : Your username or Email:

Send email to the article author

© 2021 All Rights Reserved | Iranian Journal of Information processing and Management

Designed & Developed by : Yektaweb