【摘要】 为了在大量网络Web页面中快速找到用户关心的内容,提出使用词汇之间的"相关度"来存储用户的个性化信息,应用能够在用户进行检索的过程中自动建立针对该用户的"词汇相关度"的算法设计了一个个性化元搜索引擎,并通过使用3种不同的利用词汇相关度对底层搜索引擎所返回的结果进行评估和个性化排序的算法进行实验。这里设计的个性化算法的灵敏度、抗干扰性、语义相关性分析3个指标的实验结果说明该算法最终会影响到网页的排序。基于统计方法的词汇相关度模型是一种有效的个性化信息检索技术,它可以大大提高搜索结果的质量。更多还原

【Abstract】 In order to find the content that the users care in the mass of network web pages,a method is presented by using the correlativity between words to store users’ personalized information,and using the arithmetic that can establish the "word-correlativity" of users during searching to design a personalized meta-search engine.Three methods are developed using the "Word-Correlativity" to reordering query results from underlying search engine,and testing in personalized ordering.The test results in delicacy,anti-jamming,and analyzing of word-correlativity show that this arithmetic can influence the final ordering of pages.The word-correlativity model based on statistic is an effectively personalize information searching technology.It can improve the quality of searching results greatly.更多还原