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Introduction to the special issue on statistical and probabilistic methods for user modeling

机译：用户建模的统计和概率方法特刊简介

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摘要

Statistical and probabilistic models are concerned with the use of observed sample results to make statements about unknown, dependent parameters. In user modeling, these parameters represent aspects of a user's behaviour, such as his or her goals, preferences, and forthcoming actions or locations. Recent technological advances, in particular increased computational power, together with anytime, anyplace access to computers, and the information explosion associated with the Internet, provide new opportunities for information dissemination and information gathering. On one hand, people have access to large repositories of information in digital form. On the other hand, information providers can find out more about their users' requirements by logging people's activities. This mixture of vast electronic content and increased knowledge about people's actions provides an opportunity to harness statistical and probabilistic models to build user models that support the delivery of personalized content.
机译：统计和概率模型涉及使用观察到的样本结果来做出有关未知相关参数的陈述。在用户建模中，这些参数表示用户行为的各个方面，例如他或她的目标，偏好以及即将来临的动作或位置。最近的技术进步，特别是计算能力的提高，以及随时随地对计算机的访问以及与Internet相关的信息爆炸，为信息传播和信息收集提供了新的机会。一方面，人们可以访问数字形式的大型信息库。另一方面，信息提供者可以通过记录人们的活动来找到有关其用户需求的更多信息。大量电子内容与人们对行为的了解的结合，为利用统计和概率模型建立支持个性化内容交付的用户模型提供了机会。

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