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Author Varol, Cihan ♦ Bayrak, Coskun
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Copyright Year ©2012
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Data quality ♦ Edit-distance ♦ Information quality ♦ Phonetic strategy ♦ Spelling correction
Abstract Companies acquire personal information from phone, World Wide Web, or email in order to sell or send an advertisement about their product. However, when this information is acquired, moved, copied, or edited, the data may lose its quality. Often, the use of data administrators or a tool that has limited capabilities to correct the mistyped information can cause many problems. Moreover, most of the correction techniques are particularly implemented for the words used in daily conversations. Since personal names have different characteristics compared to general text, a hybrid matching algorithm (PNRS) which employs phonetic encoding, string matching and statistical facts to provide a possible candidate for misspelled names is developed. At the end, the efficiency of the proposed algorithm is compared with other well known spelling correction techniques.
ISSN 19361955
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2012-09-01
Publisher Place New York
e-ISSN 19361963
Journal Journal of Data and Information Quality (JDIQ)
Volume Number 3
Issue Number 4
Page Count 18
Starting Page 1
Ending Page 18


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Source: ACM Digital Library