摘要
提出一种解决信息检索中信息过载问题的方案。通过对用户搜索习惯分析,发现用户对网页的选取主要依据搜索返回的网页摘要信息。分析摘要信息,运用人工智能中实例学习理论,推断用户的搜索目的。通过实例证明,该方案应用于搜索引擎,可以提高搜索引擎的查准率和智能性。
Presents a scheme to solve the question of information overload that occurred in information retrieval. Discovers most users select their needed page based on web page summarization. Analyzes it and deduces the user＇s purpose by using the case-based learning in artificial intelligence. Finally, the example shows that applying the scheme to search engine can improve the accuracy and intelligence of search engine in a certain extent.
出处
《现代计算机》
2008年第9期54-56,69,共4页
Modern Computer
关键词
实例学习
ID3算法
决策树
信息熵
Case-Based Learning
ID3 Algorithm
Decision Tree
Entropy
