基于智能学习的网络辅助浏览技术研究

随着网络信息日益庞大，人们常常为了查询某一信息而不得不从庞大的信息中人工进行搜索和挑选工作。虽然目前的搜索引擎技术大大提高了信息查询的效率，但是由于它们并非面向某个特定用户服务，所以并不能反映某个用户的特定意愿和专业领域，所得的信息往往还是有大量的冗余。提出了一种基于智能学习的网络辅助浏览技术，根据软件代理的特点，构造出网络辅助浏览代理，将网络信息进行结构化表示，利用基于关联规则的知识聚类方法，对知识元进行知识聚类，通过智能学习，使其成为个人浏览助手或者领域知识搜索专家，实现用户的个性化搜索。

Internet browsing assistant technology based on intelligent learning

With the increasing quantity of the information, it's boring and trivial to find useful items in the gigantic volume of information. Although there are several successful searching engines which promote the searching efficiency greatly now, it is difficult to fulfill people's personal searching requirement and reflect their own fields. There is often a lot of redundant information in the searching result. So the paper puts forward an Internet browsing-assisted technology based on the software agent. The agent transforms the Internet information into structured representing. Then it uses the association rules-based knowledge clustering method to classify the knowledge elements. Through intelligent learning, the agent becomes the personal browsing assistant or expert in some fields to realize the personalized searching.