Tibetan Person Attributes Extraction Based on Support Vector Machine

Abstract

Person attributes extraction is an important branch in Natural Language Processing. At present, Chinese entity attributes extraction method is mainly based on rules, statistics and machine learning methods, and has achieved good results. But the study of Tibetan entity attributes extraction has a great space. The paper uses person attribute, case-auxiliary word, verbs and other related meaningful words in Tibetan corpus as the features, and utilizes support vector machine to train and predict the classifier. It provides support for search engine, information security, machine translation and other researches.