Semantic Analysis of Web Site Audience by Integrating Web Usage Mining and Web Content Mining

摘要: With the emergence of World Wide Web, analyzing and improving Web communication has become essential to adapt content visitors’ expectations. analysis is traditionally performed by analytics software, which produce long lists page-based audience metrics. These results suffer from page synonymy, polysemy, temporality, volatility. In addition, metrics contain little semantics are too detailed be exploited organization managers chief editors, who need summarized conceptual information take high-level decisions. To obtain such metrics, we propose a method based on output mining. Output mining new kind usage mining, between our method, first collect pages server. Then, for given taxonomy covering site knwoledge domain, aggregate term weights in using OLAP tools, order topic-based representing topics. demonstrate how approach solves cited problems, compute with SQL Server Analysis Service prototype WASA real sites. Finally, compare against those obtained Google Analytics, popular tool.