SPARCL: An Improved Approach for Matching Sinhalese Words and Names in Record Clustering and Linkage

Hettiarachchi, Gayan Prasad; Attygalle, Dilhari

doi:10.1109/ghtc.2012.60

Cited by 6 publications

(9 citation statements)

References 10 publications

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“…These values are known as Soundex encodings. If Soundex encoding of any word in the post matches any Soundex encoding in the data set, then it is concluded that this post contains offensive content [33]. Table 1 presents the Soundex phonetic code for each English language letter.…”

Section: The Soundex Algorithmmentioning

confidence: 99%

Smart detection of offensive words in social media using the soundex algorithm and permuterm index

Alksasbeh

Alqaralleh

Abukhalil

et al. 2021

IJECE

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Offensive posts in the social media that are inappropriate for a specific age, level of maturity, or impression are quite often destined more to unadult than adult participants. Nowadays, the growth in the number of the masked offensive words in the social media is one of the ethically challenging problems. Thus, there has been growing interest in development of methods that can automatically detect posts with such words. This study aimed at developing a method that can detect the masked offensive words in which partial alteration of the word may trick the conventional monitoring systems when being posted on social media. The proposed method progresses in a series of phases that can be broken down into a pre-processing phase, which includes filtering, tokenization, and stemming; offensive word extraction phase, which relies on using the soundex algorithm and permuterm index; and a post-processing phase that classifies the users’ posts in order to highlight the offensive content. Accordingly, the method detects the masked offensive words in the written text, thus forbidding certain types of offensive words from being published. Results of evaluation of performance of the proposed method indicate a 99% accuracy of detection of offensive words.

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Section: The Soundex Algorithmmentioning

confidence: 99%

Smart detection of offensive words in social media using the soundex algorithm and permuterm index

Alksasbeh

Alqaralleh

Abukhalil

et al. 2021

IJECE

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show abstract

“…SoundEx is the best-known phonetic matching scheme. Developed by Odell and Russell, and patented in 1918, SoundEx uses codes based on the sound of each letter to translate a string into a canonical form of at most four characters, preserving the first letter [1] . SoundEx is a system whereby values are assigned to names in such a manner that similar-sounding names get the same value.…”

Section: A Soundex Algorithmmentioning

confidence: 99%

“…Based on the SoundEx encoding the similar sounding names would be retrieved from the large database. [1] 1. Retain the first letter of the string 2.Change all occurrences of the following letters to zero: a, e, h, i, o, u, w, y 3.…”

Section: A Soundex Algorithmmentioning

confidence: 99%

Improvement of Soundex Algorithm for Indian Language Based on Phonetic Matching

Shah¹,

Singh²

2014

IJCSEA

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“…Developed by Odell and Russell, and patented in 1918, SoundEx uses codes based on the sound of each letter to translate a string into a canonical form of at most four characters, preserving the first letter [1].…”

Section: Soundex Algorithmmentioning

confidence: 99%

“…A simple edit distance algorithm, which counts the least number of single-character insertions, deletions, and replacements needed to transform one string into another. Edit Distance could be used for phonetic matching since similar-sounding words are often spelled similarly [1]. For example, the Levenshtein distance between "bitten" and "sitting" is 3, since the following three edits change one into the other, and there is no way to do it with fewer than three edits:…”

Section: Edit Distance Algorithmmentioning

confidence: 99%

Analysis and Comparative Study on Phonetic Matching Techniques

Shah¹,

Singh²

2014

IJCA

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Searching for names in large databases containing spelling variations has always been a problem. The first solution to the problem was proposed by Robert Russell in 1912 as he proposed SoundEx algorithm. SoundEx algorithm matches the names based on the sound of the words. The technique which is based on the pronunciation of the word is known as phonetic matching. SoundEx algorithm is one of the phonetic matching algorithms. We have discussed the other phonetic matching algorithm like edit distance algorithm, K-String and Q gram algorithm, Guth algorithm, Daitch Mokotoff algorithm and Metaphone coding algorithm. Our main focus is on the SoundEx algorithm and this paper also describes the issues with SoundEx algorithm.

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SPARCL: An Improved Approach for Matching Sinhalese Words and Names in Record Clustering and Linkage

Cited by 6 publications

References 10 publications

Smart detection of offensive words in social media using the soundex algorithm and permuterm index

Smart detection of offensive words in social media using the soundex algorithm and permuterm index

Improvement of Soundex Algorithm for Indian Language Based on Phonetic Matching

Analysis and Comparative Study on Phonetic Matching Techniques

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