改善主动信息系统

Daniel Billsus, D. Hilbert, Dan Maynes-Aminzade
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引用次数: 59

摘要

主动上下文信息系统通过根据人们当前的任务或兴趣自动建议潜在的相关资源来帮助人们定位信息。这样的系统正变得越来越流行,但设计有效传达推荐信息的用户界面是一个挑战:界面必须不引人注目,但在正确的时间传达足够的信息,为用户提供价值。在本文中,我们描述了我们使用FXPAL Bar的经验,FXPAL Bar是一个主动信息系统,旨在提供对公司和个人资源的上下文访问。特别地,我们提出了三个旨在更有效地传达主动推荐的功能:半透明的推荐窗口增加了用户对特别高排名推荐的意识,查询词突出显示了推荐文档与用户当前上下文之间的关系,以及新颖的推荐摘要功能允许用户返回到最相关的先前推荐资源。我们提出了支持我们的设计决策的经验证据,并为上下文推荐系统的其他设计师提供了相关的经验教训。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving proactive information systems
Proactive contextual information systems help people locate information by automatically suggesting potentially relevant resources based on their current tasks or interests. Such systems are becoming increasingly popular, but designing user interfaces that effectively communicate recommended information is a challenge: the interface must be unobtrusive, yet communicate enough information at the right time to provide value to the user. In this paper we describe our experience with the FXPAL Bar, a proactive information system designed to provide contextual access to corporate and personal resources. In particular, we present three features designed to communicate proactive recommendations more effectively: translucent recommendation windows increase the user's awareness of particularly highly-ranked recommendations, query term highlighting communicates the relationship between a recommended document and the user's current context, and a novel recommendation digest function allows users to return to the most relevant previously recommended resources. We present empirical evidence supporting our design decisions and relate lessons learned for other designers of contextual recommendation systems.
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