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Finding keywords in blogs: Efficient keyword extraction in blog mining via user behaviors

机译：在博客中查找关键字：通过用户行为在博客挖掘中高效地提取关键字

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摘要

Readers are becoming accustomed to obtaining useful and reliable information from bloggers. To make access to the vastly increasing resource of blogs more effective, clustering is useful. Results of the literature review suggest that using linking information, keywords, or tags/categories to calculate similarity is critical for clustering. Keywords are commonly retrieved from the full text, which can be a time-consuming task if multiple articles must be processed. For tags/categories, there is also a problem of ambiguity; that is, different bloggers may define tags/categories of identical content differently. Keywords are important not only to reflect the theme of an article through blog readers' perspectives but also to accurately match users' intentions. In this paper, a tracing code is embedded in Blog Connect, a newly developed platform, to collect the keywords queried by readers and then select candidate keywords as co-keywords. The experiments show positive data to confirm that co-keywords can act as a quick path to an article. In addition, co-keyword generation can reduce the complexity and redundancy of full-text keyword retrieval procedures and satisfy blog readers' intentions.
机译：读者已习惯于从博客中获取有用和可靠的信息。为了更有效地访问大量增加的博客资源，群集非常有用。文献综述的结果表明，使用链接信息，关键字或标签/类别来计算相似性对于聚类至关重要。通常从全文检索关键字，如果必须处理多个文章，这可能是一项耗时的任务。对于标签/类别，也存在歧义的问题。也就是说，不同的博客作者可以不同地定义相同内容的标签/类别。关键字不仅对于通过博客读者的观点反映文章的主题很重要，而且对于准确匹配用户的意图也很重要。本文将跟踪代码嵌入到新开发的平台Blog Connect中，以收集读者查询的关键字，然后选择候选关键字作为联合关键字。实验显示出积极的数据，证实了共同关键字可以充当文章的快速路径。此外，共关键字生成可以降低全文关键字检索过程的复杂性和冗余度，并满足博客读者的意图。

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