Semantic Categorization of Contextual Features Based on Wordnet for G-to-P Conversion of Arabic Numerals Combined with Homographic Classifiers

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• 作者：Youngim Jung ; Aesun Yoon ; Hyuk-Chul Kwon
• 刊名：Lecture Notes in Computer Science
• 出版年：2005
• 出版时间：2005
• 年：2005
• 卷：3689
• 期：1
• 页码：pp.595-600
• 全文大小：179 KB
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

Arabic numerals show a high occurrence-frequency and deliver significant senses, especially in scientific or informative texts. The problem, how to convert Arabic numerals to phonemes with ambiguous classifiers in Korean, is not easily resolved. In this paper, the ambiguities of Arabic numerals combined with homographic classifiers are analyzed and the resolutions for their sense disambiguation based on KorLex ( Korean Lexico-Semantic Network) are proposed. Words proceeding or following the Arabic Numerals are categorized into 54 semantic classes based on the lexical hierarchy in KorLex 1.0. The semantic classes are trained to classify the meaning and the reading of Arabic Numerals using a decision tree. The proposed model shows 87.3% accuracy which is 14.1% higher than the baseline.