DocumentCode
2033267
Title
Classification of brand names based on n-grams
Author
Warintarawej, P. ; Laurent, A. ; Pompidor, P. ; Laurent, B.
Author_Institution
LIRMM, Univ. Montpellier 2, Montpellier, France
fYear
2010
fDate
7-10 Dec. 2010
Firstpage
12
Lastpage
17
Abstract
Supervised classification has been extensively addressed in the literature as it has many applications, especially for text categorization or web content mining where data are organized through a hierarchy. On the other hand, the automatic analysis of brand names can be viewed as a special case of text management, although such names are very different from classical data. They are indeed often neologisms, and cannot be easily managed by existing NLP tools. In our framework, we aim at automatically analyzing such names and at determining to which extent they are related to some concepts that are hierarchically organized. The system is based on the use of character n-grams. The targeted system is meant to help, for instance, to automatically determine whether a name sounds like being related to ecology.
Keywords
data mining; learning (artificial intelligence); marketing; pattern classification; text analysis; Web content mining; brand name classification; n-grams; supervised classification; text categorization; text management; Accuracy; Buildings; Companies; Pattern recognition; Thesauri; Training; Training data; Brand Names; Hierarchies; Textual Classification; n-grams;
fLanguage
English
Publisher
ieee
Conference_Titel
Soft Computing and Pattern Recognition (SoCPaR), 2010 International Conference of
Conference_Location
Paris
Print_ISBN
978-1-4244-7897-2
Type
conf
DOI
10.1109/SOCPAR.2010.5685842
Filename
5685842
Link To Document