Multi-level Linguistic Knowledge Based Chinese Grapheme-to-Phoneme Conversion

Author(s):  
Yi Liu ◽  
Xiaojun Chen ◽  
Caixia Gong ◽  
Xihong Wu
2018 ◽  
Vol 51 (6) ◽  
pp. 797-814 ◽  
Author(s):  
David Bendig ◽  
Steffen Strese ◽  
Tessa C. Flatten ◽  
Maika Eva Susanne da Costa ◽  
Malte Brettel

2012 ◽  
Vol 3 (3) ◽  
pp. 58-67 ◽  
Author(s):  
Hesham Bin-Abbas ◽  
Saad Haj Bakry

Building a knowledge-based society is widely recognized as leading to human, social and economic benefits. This paper explores the issue of using knowledge management as an instrument for the development and sustainability of this knowledge society. The paper attempts to achieve its purpose through four main integrated steps: providing a brief review of knowledge management and the knowledge society; viewing knowledge management according to the STOPE “strategy, technology, organization, people and the environment” scope; incorporating knowledge management into the six-sigma DMAIC “define, measure, analyze, improve, and control” process; and deriving observations on the outcome, and producing guidelines for future work. The paper emphasizes the claim that developing and continuously sustaining the knowledge society can be achieved by applying knowledge management through building it into the STOPE scope and the six-sigma process, and by considering the multi-level nature of the society. The paper enjoys a high potential as a guide to knowledge management driven development and sustainability of the knowledge society at all levels. This would be beneficial to all those interested and concerned with supporting the role of knowledge in their own societies.


2016 ◽  
Vol 8 (1) ◽  
pp. 165-172
Author(s):  
Eniafe Festus Ayetiran ◽  
Kehinde Agbele

Abstract Computational complexity is a characteristic of almost all Lesk-based algorithms for word sense disambiguation (WSD). In this paper, we address this issue by developing a simple and optimized variant of the algorithm using topic composition in documents based on the theory underlying topic models. The knowledge resource adopted is the English WordNet enriched with linguistic knowledge from Wikipedia and Semcor corpus. Besides the algorithm’s eficiency, we also evaluate its efectiveness using two datasets; a general domain dataset and domain-specific dataset. The algorithm achieves a superior performance on the general domain dataset and superior performance for knowledge-based techniques on the domain-specific dataset.


2020 ◽  
Vol 50 (12) ◽  
pp. 4616-4630
Author(s):  
Toqir A. Rana ◽  
Yu-N Cheah ◽  
Tauseef Rana
Keyword(s):  

2019 ◽  
Vol 162 ◽  
pp. 916-923
Author(s):  
Álvaro Tejeda-Lorente ◽  
Juan Bernabé-Moreno ◽  
Julio Herce-Zelaya ◽  
Carlos Porcel ◽  
Enrique Herrera-Viedma

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