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[DOC File]A Fuzzy Extension of Description Logics - WSEAS
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Finally, our plans are to extend the existed tableaux algorithm to support the proposed fuzzy extensions of DLs. In [19] and [20] are defined complete algorithms for solving a set of the fuzzy extensions. Our premise is to extent the fuzzy tableaux algorithm to support the whole set of t-norms and s-norm operators. References:
fuzzy name matching

[DOC File]1 - WSEAS
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From all the fuzzy techniques that have been developed, the fuzzy c-means algorithm is probably the most widely used. Fuzzy c-means (FCM) is a method of clustering which allows one piece of data to belong to two or more clusters [16]. This method is frequently used in pattern recognition.
name matching algorithm

[DOCX File]Introduction - Global Trade Analysis Project (GTAP)
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These legal names (with legal jurisdiction used to filter and improve matching opportunities) are applied to a fuzzy matching routine to determine the most likely PermID within the Organisation PermID database corresponds with this name. The linking of Legal Name to an underlying PermID uses the PermID Record Matching service. https://permid ...
fuzzy match algorithm

Software tools for integration methodologies
Conventional "fuzzy matching" technology is computer-resource intensive: rule sets often drive multiple queries on databases, as developers compensate for the lack of sophisticated matching technology using multiple "wildcard" searches, or testing validity of error-prone algorithms such as Soundex.
name and address matching algorithms

[DOC File]2
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The Fuzzy group then picked up the SQL generated from the file and the fuzzy words from files. Based on the fuzzy word the appropriate “and clause” was then added to the SQL. SELECT DISTINCT person.name,has.[EYE.Color] FROM Person,has,Person LEFT Join has Person.ID WHERE has.[EYE Color] = “ Brown” and weight = 0.7.
name matching algorithm python

[DOC File]SAS Data Quality – Cleanse: Techniques for Merge/Purge on ...
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If data is standardized, most matching involves simple exact matches. Standardization will not correct typos, but will unify the different forms of a first name. Still, fuzzy matching remains very important. Without well-conceived fuzzy match algorithms, the result is likely to be unsatisfactory, with too many false positives and/or false ...
python fuzzy name matching

Memorandum United States Department of Education
OFAC’s Sanction List Search (SLS) combines two fuzzy-matching algorithms – Jaro-Winkler and Soundex – with two matching techniques – name elements and full name – to calculate a single match score, expressed as a match “percentage.” Likewise, in our matching we used both algorithms and two similar matching strategies.
fuzzy search algorithm

[DOC File]Growing the Semantic Web - Brigham Young University
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Matching the query name JENS PEDERSEN BACH to JENS BACHIS in the record as a variant form [NAME] ... The fuzzy search algorithm puts the best matches at the top of the list, but retrieves records that only somewhat match at the bottom rather than eliminate poorer matches too soon. The trick then is to set the threshold not so high as to ...
fuzzy matching algorithm

[DOCX File]Executive Summary - UK Statistics Authority
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Using the 15 groups above as blocking passes, together with a fuzzy match on name Two names are considered to be a fuzzy match if the standardised Levenshtein edit distance between them is greater than 0.6 meaning that at least 60% of the characters match.
fuzzy name matching

[DOC File]Using Fuzzy k-Modes to Analyze Patterns of System Calls ...
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The fuzzy version of the k-modes algorithm was first proposed by Zhexue Huang and Michael K. Ng in their paper “A Fuzzy k-Modes Algorithm for Clustering Categorical Data” as an extension for the fuzzy c-means algorithm. The fuzzy c-means algorithm is the most prominent fuzzy clustering algorithm [24] The fuzzy k-modes algorithm was ...
name matching algorithm

Fuzzy name matching algorithm