个性化网络搜索的挑战和最新趋势:一项调查

K. Selvakumar, S. Sendhilkumar
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引用次数: 4

摘要

在过去十年中,Web的指数级增长使其成为世界上最大的公共可用数据源。它集成了文本、图形、音频、视频和超文本。网络用户使用多种搜索技术来访问万维网(WWW)上的海量信息。网络搜索是从成堆的文档、网页和Web资源中查找信息的过程。搜索引擎在网络搜索过程中起着至关重要的作用。但是网络用户和他们的基本内容可能彼此不同。此外,用户在处理他们想要的内容时,也在努力获取最重要的信息。本文的主要目的是对使用Web挖掘技术的Web搜索概念进行比较分析。本文还重点介绍了历史上模糊神经网络方法在增强Web搜索方面的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges and recent trends in personalized Web search: A survey
The exponential growth of the Web in last decade makes the largest publically available data source in the world. It integrates text, graphics, audio, video and hypertext. Web users approaches many searching techniques to access the enormous information available on the World Wide Web (WWW). Web search is a process to find information from the pile of documents, Web pages and Web sources. Search engines are playing vital role in Web search process. But the Web users and their essential content may vary among one another. Moreover the users are struggling for obtaining the most significant information while processing their desire content. The main objective of this paper is to provide a comparative analysis of the Web search concepts using Web mining techniques. This paper also highlights the Fuzzy Neural Networks approach in the history for enhancing Web search.
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