原名「台灣學術線上」
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1
題名:Linking Databases using Matched Arabic Names     (42點)
著者:Tarek El-Shishtawy
出版地區:台灣
出版城市:台北市
學科:電機資訊
關鍵字:Name Matching ; Record Linkage ; Data Integration ; Arabic NLP ; Information Retrieval
刊名:International Journal of Computational Linguistics & Chinese Language Processing
卷期:19卷1期(2014.3)
頁碼:33-53
語言:英語
摘要: 英文摘要PDF

In this paper, a new hybrid algorithm that combines both token-based and character-based approaches is presented. The basic Levenshtein approach also has been extended to the token-based distance metric. The distance metric is enhanced to set the proper granularity level behavior of the algorithm. It smoothly maps a threshold of misspelling differences at the character level and the importance of token level errors in terms of token position and frequency.
Using a large Arabic dataset, the experimental results show that the proposed algorithm successfully overcomes many types of errors, such as typographical errors, omission or insertion of middle name components, omission of non-significant popular name, and different writing style character variations. When compared with other classical algorithms, using the same dataset, the proposed algorithm was found to increase the minimum success level of the best tested lower limit algorithm (Soft TFIDF) from 69% to about 80%, while achieving an upper accuracy level of 99.67%.


    

本卷期目次
International Journal of Computational Linguistics & Chinese Language Processing 19卷1期 (2014.3)
A Novel Approach for Handling Unknown Word Problem in Chinese-Vietnamese Machine Translation/ Phuoc TranDien Dinh
Joint Learning of Entity Linking Constraints Using a Markov-Logic Network/ Hong-Jie DaiRichard Tzong-Han TsaiWen-Lian Hsu
Linking Databases using Matched Arabic Names/ Tarek El-Shishtawy
On the Use of Speech Recognition Techniques to Identify Bird Species/ Wei-Ho TsaiYu-Zhi Xue
 
   
 
   

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