关键词: 最大频繁序列模式, 个性化推荐, 横向推荐, 纵向推荐

Abstract: A technology based on maximal frequent sequential pattern direct graph is presented to perform personalization recommendation.Because of taking the access sequence of pageviews into account in this technology，a higher accuracy can be obtained.Direct graph structure compresses and stores all maximal frequent sequences discovered from Web usage mining，recommendation engine matches some sub paths of the direct graph and has a recomentdation both on breadthwise and lengthways according to nearest access subsequence form user active session，without need to find the identical or similar patterns in the whole pattern database，which enormously improves the speed of patterns matching to satisfy the need and specific of real-time recommendation better.The results of experiments show that the approach is effective in speed and precision.

Key words: maximal frequent sequential pattern, personalization recommendation, breadthwise recommendation, lengthways recommendation