Wenfang Cheng^1,2*, Qing’e Wu^3,4, Xiao Cheng⁵, Jie Zhang^1,2, Zhuanling Song⁶

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¹ Polar Research Institute of China, Shanghai, China.
² Key Laboratory for Polar Science, State Oceanic Administration, Shanghai, China.
³ School of Computer Science, Fudan University, Shanghai, China.
⁴ College of Electric and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, China.
⁵ College of Global Change and Earth System Science, Beijing Normal University, Beijing, China.
⁶ The First Institute of Oceanography, SOA, Qingdao, China.
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Abstract: 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.

Keywords: Search Engine, Fuzzy Query, Semantic Similarity, Wiki

Cite this paper: Cheng, W. , Wu, Q. , Cheng, X. , Zhang, J. , Song, Z. (2015) DBpedia-Based Fuzzy Query Recommenda-tion Algorithm and Its Applications in the Resource-Sharing Platform of Polar Samples. International Journal of Intelligence Science, 5, 196-207. doi: 10.4236/ijis.2015.55017.

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