With the development of the Internet and the accumulation of information on the web, users use a search engine to easily obtain the desired information. A query suggestion is one of the main services provided by a search engine, and is very important for improving search performance, creating efficient queries, and reducing search time. However, there are search engines that do not support the query suggestion service. Under such engines, if users want to perform a search, they would have much difficulties in effectively performing the search. In this paper, to tackle the problem, we propose and develop a metasuggestion engine that crawls suggested search queries from search engines with a suggestion service, applies a re-ranking algorithm, and provides the suggested search queries in the form of an extension program on a web browser. Meta-suggestion engine are useful for users searching in engines that do not provide query suggestions, as they provide query suggestions wherever the user searches. We evaluate engines with relevance-based and predictive hit-based evaluation methods, showing that MSE produces good quality suggestions. We study improvements in target engine selection and re-ranking algorithms in future studies.
翻译:随着互联网的发展和网上信息的积累,用户使用搜索引擎来方便地获取所需信息。查询建议是搜索引擎提供的主要服务之一,对于提高搜索性能、创造高效查询和缩短搜索时间非常重要。然而,有些搜索引擎并不支持查询建议服务。在这种引擎下,如果用户想要进行搜索,他们就会很难有效地进行搜索。在本文件中,为了解决这一问题,我们提议并开发一个元缩略图引擎,该引擎通过建议使用建议服务从搜索引擎查询查询,采用重新排档算法,并以扩展程序的形式在网络浏览器上提供建议的查询查询查询查询查询查询。元缩略图引擎对于在用户搜索的任何地方都提供查询建议而不提供查询建议的用户来说非常有用。我们用基于相关性和预测的基于打击的评价方法对引擎进行评价,表明MSE提出了高质量的建议。我们研究目标引擎选择和今后研究中的重新排序算法的改进。