DBpedia-Based Fuzzy Query Recommenda-tion Algorithm and Its Applications in the Resource-Sharing Platform of Polar Samples

• 作者: Jie Zhang Qing’e Wu Wenfang Cheng Xiao Cheng Zhuanling Song
• 来源期刊: 智能科学国际期刊(英文)
• 学科: 工学
• 关键词: Search Engine Fuzzy QUERY SEMANTIC Similarity WIKI
• 年，卷（期）: 2015,（5）
• 页码范围: 196-207
• 页数: 12页
• 分类号: TP39

摘要

In order to continuously promote the polar sample resource services in China and effectively guide the users to access such information as needed, a fuzzy algorithm based on DBpedia has been proposed through the analysis of the characteristics of the query recommendations in search engines, namely, to search similar entry queues by constructing a DBpedia category tree, then use the fuzzy matching algorithm to work out the entry similarity, and then present the example query applications of this algorithm on the resource-sharing platform of polar samples. Comparing the traditional literal character matching method and DBpedia semantic similarity algorithm, the experimental results show that the fuzzy query algorithm based on DBpedia features has a higher search accuracy rate, stronger anti-interference capability, and more flexible algorithm use by virtue of its fuzzy weight adjustment.