Recent proposal have suggested web usage mining as an enabling mechanism to overcome the problem associated with more traditional web personalization techniques such as collaborative or content - based filtering . these problems include lack of scalability . reliance on subjective user ratings or static profiles , and the inability to capture a richer set of semantic relationships among objects . yet , usage - based personalization can be problematic when little usage data is available pertaining to some objects or when the site content changes regularly . for more effective personalization , both usage and content attributes of a site should be integrated into a web minging framwork and used by the recommendation engine in a uniform manner 為解決傳統(tǒng)技術(shù)中出現(xiàn)的這些問題,一些研究提出將web使用日志的挖掘應(yīng)用到個人化技術(shù)中。 web使用記錄的挖掘雖然有諸多的優(yōu)點,卻不能適應(yīng)用戶的使用信息較難獲取及站點內(nèi)容經(jīng)常變化的情況。為了使個人化系統(tǒng)更有效,我們需要將web使用記錄的挖掘與web內(nèi)容挖掘集成到同一個結(jié)構(gòu)中,由推薦引擎以統(tǒng)一的方式使用他們。