Query-driven approach of contextual ontology module learning using web snippets
Query-driven approach of contextual ontology module learning using web snippets
复制标题
使用网络片段进行上下文本体模块学习的查询驱动方法
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
H. Ghézala
中科院分区：
文献类型：
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作者：
Nesrine Ben Mustapha;Marie;H. B. Zghal;H. Ghézala
这项工作的主要目标是自动构建本体模块，覆盖搜索用户在基于本体的问题回答在Web上的条款。事实上，一些出现的本体模块提取的方法旨在解决识别与应用相关的本体片段候选者的问题。主要的问题是，这些方法只考虑输入的预定义的本体，而不是在文本中表示的底层语义。这项工作提出了一种上下文本体模块学习的方法，通过分析过去的用户查询和搜索传统搜索引擎提供的网页片段，覆盖特定的搜索词。所获得的上下文模块将用于查询重构。该建议已被评估的两个标准的基础上：发现的本体模块的语义cotopy措施和通过使用所产生的本体模块查询重构获得的搜索结果的精度测量。实验已经进行了根据两个案例研究：一个开放域的网络搜索和医学数字图书馆“PubMed”。
The main objective of this work is to automatically build ontology modules that cover search terms of users in ontology-based question answering on the Web. Indeed, some arising approaches of ontology module extraction aim at solving the problem of identifying ontology fragment candidates that are relevant for the application. The main problem is that these approaches consider only the input of predefined ontologies, instead of the underlying semantics represented in texts. This work proposes an approach of contextual ontology module learning covering particular search terms by analyzing past user queries and by searching for web snippets provided by the traditional search engines. The obtained contextual modules will be used for query reformulation. The proposal has been evaluated on the ground of two criteria: the semantic cotopy measure of discovered ontology modules and the precision measure of the search results obtained by using the resulted ontology modules for query reformulation. The experiments have been carried out according to two case studies: an open domain web search and the medical digital library “PubMed”.