PRESY：一个基于上下文的Web信息检索查询重构工具
PRESY: A Context Based Query Reformulation Tool for Information Retrieval on the Web
摘要：
问题陈述：网络上的海量信息以及新用户的不断增长给信息检索带来了新的挑战。这些用户越来越难以找到满足其个人需要的相关文件。当然，目前的搜索引擎（如谷歌，必应和雅虎）提供了一个有效的方式来浏览网页内容。然而，结果质量高度依赖于使用查询，这些查询需要更精确地找到相关文档。对于大多数不熟练的用户来说，这项任务仍然很复杂，他们无法在查询中用重要的词来表达自己的需求。因此，我们认为，重新制定的初始用户的查询可以是一个很好的替代方案，以提高信息的选择性。本研究提出一种新的方法，并提出了一个原型系统称为PRESY（Profile-based REformulation SYSTEM）的信息检索在Web上。方法：它使用增量方法通过构建上下文基础来对用户进行分类。后者是由两种类型的上下文（静态和动态）使用用户的配置文件获得。提出的架构实现使用.NET环境进行查询重构测试。结果：实验结果表明，该方法有效地提高了返回内容的精度。这些测试是用最流行的搜索引擎（即谷歌，绑定和雅虎）进行的，特别是因为它们的高选择性。在给定的结果中，我们发现查询重构提高了前三个结果的10.7%和11.7%的下七个返回的元素。因此，我们可以看到，用户初始查询的重新表达提高了返回内容的相关性。
英文摘要：
Problem Statement: The huge number of information on the web as well as the growth of new inexperienced users creates new challenges for information retrieval. It has become increasingly difficult for these users to find relevant documents that satisfy their individual needs. Certainly the current search engines (such as Google, Bing and Yahoo) offer an efficient way to browse the web content. However, the result quality is highly based on uses queries which need to be more precise to find relevant documents. This task still complicated for the majority of inept users who cannot express their needs with significant words in the query. For that reason, we believe that a reformulation of the initial user's query can be a good alternative to improve the information selectivity. This study proposes a novel approach and presents a prototype system called PRESY (Profile-based REformulation SYstem) for information retrieval on the web. Approach: It uses an incremental approach to categorize users by constructing a contextual base. The latter is composed of two types of context (static and dynamic) obtained using the users' profiles. The architecture proposed was implemented using .Net environment to perform queries reformulating tests. Results: The experiments gives at the end of this article show that the precision of the returned content is effectively improved. The tests were performed with the most popular searching engine (i.e. Google, Bind and Yahoo) selected in particular for their high selectivity. Among the given results, we found that query reformulation improve the first three results by 10.7% and 11.7% of the next seven returned elements. So as we can see the reformulation of users' initial queries improves the pertinence of returned content.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
