Improving the Performance of Wikipedia Based on the Entry Relationship between Articles,ERICDATA高等教育知識庫
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篇名
Improving the Performance of Wikipedia Based on the Entry Relationship between Articles
並列篇名
Improving the Performance of Wikipedia Based on the Entry Relationship between Articles
作者 Lin-Chih Chen
英文摘要

Wikipedia is the largest online encyclopedia in the world. It is free to access by anyone and its main advantage is that it can also be edited by any person at any time. On the one hand, this caused a rapid growth to its number of available articles and languages. It is likely to cause that most users are difficult to differentiate various synonymy and polysemy terms from the millions of articles in Wikipedia. On the other hand, traditional semantic analysis models are mainly focus on to deal with the semantic relationships between terms, or terms and documents. However, these models are lacking to deal with the semantic relationships between documents.

In this paper, to enhance the semantic relationships between documents, we use the entry relationship between any two Wikipedia articles to design our Latent Entry Analysis (LEA) model. The advantages of LEA have the following several aspects: (1) it can effectively deal with the problems of synonymy and polysemy; (2) it is a good model to find the semantic relationships between terms, terms and documents, or documents; (3) it is a good model with a high-performance and low-cost compared to other semantic analysis models; (4) it is a suitable model to effectively handle big data sets in Wikipedia.

起訖頁 711-723
關鍵詞 Wikipedia articlesEntry relationshipOnline internet encyclopediaSemantic analysis modelsAspect model
刊名 網際網路技術學刊  
期數 201805 (19:3期)
出版單位 台灣學術網路管理委員會
DOI 10.3966/160792642018051903009  複製DOI
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