Extracting Facets from Textual Contents for Faceted Search over XML Data
Extracting Facets from Textual Contents for Faceted Search over XML Data
复制标题
从文本内容中提取分面以通过 XML 数据进行分面搜索
DOI：
10.1145/2684200.2684294
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Toshiyuki Amagasa and Hiroyuki Kitagawa
中科院分区：
文献类型：
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作者：
Takahiro Komamizu;Toshiyuki Amagasa and Hiroyuki Kitagawa
XML数据分面搜索是一种很有前途的搜索方法，它可以从给定的XML数据中找到所需的子树，具有很高的可用性。本文提出了一种改进的XML数据分面搜索方法，利用包含独特的和较长的文本值，如文献数据库中的论文标题的方面。我们的方法是提取合适的条款，将当前的结果分为几组。提出了一种通过定义任务的特异性来评价探索性搜索的任务设计方法，并介绍了如何生成具有给定特异性的任务。通过这种任务设计，我们评估了我们提出的方法，结果表明，我们提出的方法与以前的方法相比，提高了搜索性能，特别是当任务具有低规格水平。
Faceted search for XML data is one of the promising exploration methods with high usability to find desired subtrees from a given XML data. This paper proposes improved approach of faceted search over XML data by utilizing facets containing unique and longer textual values, like titles of papers in bibliographic database. Our approach is to extract suitable terms which categorize the current results into several groups. Also we propose a task designing method for evaluating exploratory search by defining specificity of tasks called specification level, and we introduce how to generate tasks with given specification level as well. With this task design, we evaluate our proposed approach and the results show our proposed approach improves search performance comparing with the previous approaches, especially when tasks have low specification levels.