从多维查询模型构建MultiView分析师档案：从主观到主观偏好
Building MultiView Analyst Profile From Multidimensional Query Logs: From Consensual to Conflicting Preferences
摘要：
为了给分析者提供合适的结果，用户偏好摘要被广泛应用于多个领域。本文介绍了一种从OLAP查询日志中构造用户简档的新方法。其核心思想是通过从OLAP日志中提取证据来了解用户的偏好。事实上，分析师的偏好分为三个主要池：（i）一致或非冲突的偏好，指的是所有分析师的相同偏好;（ii）半冲突的偏好，对应于一些分析师的相似偏好;（iii）冲突的偏好，与所有分析师的不相交的偏好。为了建立通用的和全局的模型，准确地描述分析师，我们丰富了所获得的特性，通过包括几个视图，即个人视图，专业视图和行为视图。然后，对从多维数据库中提取的多视图轮廓进行标注。
英文摘要：
In order to provide suitable results to the analyst needs, user preferences summarization is widely used in several domains. In this paper, we introduce a new approach for user profile construction from OLAP query logs. The key idea is to learn the user's preferences by drawing the evidence from OLAP logs. In fact, the analyst preferences are clustered into three main pools : (i) consensual or non conflicting preferences referring to same preferences for all analysts; (ii) semi-conflicting preferences corresponding to similar preferences for some analysts; (iii) conflicting preferences related to disjoint preferences for all analysts. To build generic and global model accurately describing the analyst, we enrich the obtained characteristics through including several views, namely the personal view, the professional view and the behavioral view. After that, the multiview profile extracted from multidimensional database can be annotated.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
