Extracting Named Entities Using Support Vector Machines

2006 ◽  
pp. 91-103 ◽  
Author(s):  
Yu-Chieh Wu ◽  
Teng-Kai Fan ◽  
Yue-Shi Lee ◽  
Show-Jane Yen
Keyword(s):  
Support Vector Machines ◽  
Support Vector ◽  
Named Entities ◽  
Vector Machines

scholarly journals Developing classification-based named entity recognizers (NER) for Sambalpuri and Odia applying support vector machines (SVM)

2018 ◽  
pp. 1-7
Author(s):  
Pitambar Behera ◽  
Sharmin Muzaffar
Keyword(s):  
Support Vector Machines ◽  
Support Vector ◽  
Named Entities ◽  
Named Entity ◽  
Vector Machines

This paper demonstrates the development of named Entity Recognizers (NER) applying Support Vector Machines (SVM) for Sambalpuri and Odia. The Sambalpuri corpus amounts to 112k word tokens out of which 5,887 are named entities. On the contrary, 250k ILCI corpus has been applied for Odia out of which 18,447 tokens are named entities. The former accurately recognizes 96.72% whereas the latter provides 98.10% accuracy.

Soft Biometrics Classification Using Denoising Convolutional Autoencoders and Support Vector Machines

2018 ◽  
Author(s):  
Nelson Marcelo Romero Aquino ◽  
Matheus Gutoski ◽  
Leandro Takeshi Hattori ◽  
Heitor Silvério Lopes
Keyword(s):  
Support Vector Machines ◽  
Support Vector ◽  
Soft Biometrics ◽  
Vector Machines

scholarly journals Classification of hyperspectral endocrine tissue images using support vector machines

2020 ◽  
Vol 16 (5) ◽  
pp. 1-10
Author(s):  
Marianne Maktabi ◽  
Hannes Köhler ◽  
Magarita Ivanova ◽  
Thomas Neumuth ◽  
Nada Rayes ◽  
...  
Keyword(s):  
Support Vector Machines ◽  
Support Vector ◽  
Endocrine Tissue ◽  
Vector Machines
Sign in / Sign up

Export Citation Format

Share Document