Semantic Web Technology to Build the Article Content Objects of the Trust Evaluation Methods

• Main Authors: Jia-Da Yeh, 葉佳達
• Other Authors: Ching-Long Yeh
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/18469878225344750333

碩士 === 大同大學 === 資訊工程學系(所) === 98 === The rise of Wikipedia, let us insight into the power of the co-authoring, but also because it is of the co-authoring, so that we can not help but to question it, it's the article quality is really reliable? Will not be part of everyday nonsense? Many studies for the Wikipedia proposed trust evaluation mechanism, trying to find out which rules, test articles, to help readers choose a good article to read, to avoid shoddy article. The most common assessment method is to use the credit accumulation system and the observation of the background of the article (Editor frequency, number of discussion, etc.), but the evaluation method for the content of the article is slightly scarce, we believe that the semantic content of the article should be the most important clues. Therefore, in this paper, we propose a trust evaluation mechanisms based on semantic content of the article. We choose two wiki community which use Semantic Web technology as our subjects, DBpedia and Freebase respectively. With Semantic Web technology, the article content to be structured, so the machine can handle semantic content of the article, to help us deal with the trust evaluation of semantic computing. We use the concept of PageRank as a basis for our trust evaluation method. We use DBpedia which has high quality knowledge content as the score sheet, score Freebase article with DBpedia semantic content of the degree of similarity, that is, how many hyperlinks that Freebase accepted from DBpedia as the recommendation. We implemented a system that allows users to browse Freebase entry page, through some simple operations, users can get the trust assessment of the article, help users determine the quality of the article, choose a good article to reading.