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Footprints of information foragers: behaviour semantics of visual exploration

机译:信息觅食者的足迹:视觉探索的行为语义

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Social navigation exploits the knowledge and experience of peer users of information resources. A wide variety of visual-spatial approaches become increasingly popular as a means to optimize information access as well as to foster and sustain a virtual community among geographically distributed users. An information landscape is among the most appealing design options of representing and communicating the essence of distributed information resources to users. A fundamental and challenging issue is how an information landscape can be designed such that it will not only preserve the essence of the underlying information structure, but also accommodate the diversity of individual users. The majority of research in social navigation has been focusing on how to extract useful information from what is in common between users' profiles, their interests and preferences. In this article, we explore the role of modelling sequential behaviour patterns of users in augmenting social navigation in thematic landscapes. In particular, we compare and analyse the trails of individual users in thematic spaces along with their cognitive ability measures. We are interested in whether such trails can provide useful guidance for social navigation if they are embedded in a visual-spatial environment. Furthermore, we are interested in whether such information can help users to learn from each other, for example, from the ones who have been successful in retrieving documents. In this article, we first describe how users' trails in sessions of an experimental study of visual information retrieval can be characterized by Hidden Markov Models. Trails of users with the most successful retrieval performance are used to estimate parameters of such models. Optimal virtual trails generated from the models are visualized and animated as if they were actual trails of individual users in order to highlight behavioural patterns that may foster social navigation. The findings of the research will provide direct input to the design of social navigation systems as well as to enrich theories of social navigation in a wider context. These findings will lead to the further development and consolidation of a tightly coupled paradigm of spatial, semantic and social navigation. (C) 2002 Elsevier Science Ltd. All rights reserved. [References: 30]
机译:社交导航利用信息资源的对等用户的知识和经验。作为优化信息访问以及在地理上分散的用户之间建立和维持虚拟社区的一种手段,各种各样的视觉空间方法变得越来越流行。信息格局是代表和向用户传达分布式信息资源的实质的最吸引人的设计方案之一。一个基本且具有挑战性的问题是如何设计一种信息格局,使其不仅保留基础信息结构的本质,而且还要适应各个用户的多样性。社会导航的大多数研究都集中在如何从用户的个人资料,他们的兴趣和偏好之间的共同点中提取有用的信息。在本文中,我们探讨了对用户的顺序行为模式进行建模在增强主题景观中的社交导航方面的作用。特别是,我们比较并分析了主题空间中单个用户的踪迹以及他们的认知能力测度。我们感兴趣的是,如果将这些线索嵌入视觉空间环境中,它们是否可以为社交导航提供有用的指导。此外,我们感兴趣的是这些信息是否可以帮助用户彼此学习,例如,从成功检索文档的人那里学习。在本文中,我们首先描述如何通过隐马尔可夫模型表征视觉信息检索实验研究中用户的踪迹。具有最成功的检索性能的用户踪迹用于估计此类模型的参数。从模型生成的最佳虚拟轨迹将被可视化和动画化,就好像它们是单个用户的实际轨迹一样,以便突出可能促进社交导航的行为模式。研究结果将为社会导航系统的设计提供直接投入,并在更广泛的背景下丰富社会导航的理论。这些发现将导致空间,语义和社交导航紧密耦合的范例的进一步发展和巩固。 (C)2002 Elsevier ScienceLtd。保留所有权利。 [参考:30]

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