Title :
Identification of relations from IndoWordNet for Indian languages using Support Vector Machine
Author :
Megha Garg;Bhaskar Sinha;Somnath Chandra
Author_Institution :
Department of Electronics and Information Technology, New Delhi, India
Abstract :
Identification and classification of relations between synsets in a low resource language is a challenging and difficult task, which requires intensive Natural Language Processing (NLP). This paper presents Support Vector Machine (SVM) based approach for learning, classifying and automatically predicting relationships between Hindi Synsets. The average accuracy obtained using SVM is 71.87%, which can be further improved through introduction of language based knowledge. The system performance has been validated using the performance measures namely Precision, Recall and F-score.
Keywords :
"Support vector machines","Training","Semantics","Feature extraction","Databases","Metadata","Natural language processing"
Conference_Titel :
Computing and Network Communications (CoCoNet), 2015 International Conference on
DOI :
10.1109/CoCoNet.2015.7411241