Paper Info
Title
Introducing Uws - A Fuzzy Based Word Similarity Function With Good Discrimination Capability: Preliminary Results
Abstract
This paper introduces a novel word similarity function, the Uke Similarity Function (UWS), that fuses the most interesting characteristics of the two main philosophies in word and string matching: the edit distance and the n-gram similarity approach. It also uses fuzzy sets to integrate expert knowledge about typographical errors and to easily include phonetic and token related errors. The UWS was developed with the goal of automatic detection and correction of typographical and other word errors in unedited corpus data when creating word lists.
Year
DOI
Venue
2013
10.1109/FUZZ-IEEE.2013.6622494
2013 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ - IEEE 2013)
Keywords
Field
DocType
Word Similarity, Word Matching, Fuzzy Sets, Typographical Error Detection and Correction, Unedited Corpus Data
String searching algorithm,Edit distance,Computer science,Fuzzy logic,Fuzzy set,Speech recognition,Artificial intelligence,Natural language processing,Fuse (electrical),Typographical error,Security token,Machine learning
Conference
ISSN
Citations 
PageRank 
1098-7584
8
0.59
References 
Authors
8
2
Name
Order
Citations
PageRank
João Paulo Carvalho111017.52
Luísa Coheur219934.38