Frequent Patterns Based Word Network: What Can We Obtain from the Tourism Blogs?
作者： Hua Yuan , Lei Guo , Hualin Xu , Yong Xiang
DOI: 10.1007/978-3-642-39787-5_2
关键词:
摘要: In this work, we present a method to extract interesting information for specific reader from massive tourism blog data. To end, first introduce the web crawler tool obtain contents and divide them into semantic word segments. Then, use frequent pattern mining discover useful 1- 2-itemset between words after necessary data cleaning. Third, visualize all correlations with network. Finally, propose local search based on max-confidence measurement that enables readers specify an topic find relevant contents. We illustrate benefits of approach by applying it Chinese online dataset.
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