TaskTracer: a desktop environment to support multi-tasking knowledge workers

Anton N. Dragunov, Thomas G. Dietterich, Kevin Johnsrude, Matthew R. McLaughlin, Lida Li, Jonathan L. Herlocker
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引用次数: 280

Abstract

This paper reports on TaskTracer --- a software system being designed to help highly multitasking knowledge workers rapidly locate, discover, and reuse past processes they used to successfully complete tasks. The system monitors users' interaction with a computer, collects detailed records of users' activities and resources accessed, associates (automatically or with users' assistance) each interaction event with a particular task, enables users to access records of past activities and quickly restore task contexts. We present a novel Publisher-Subscriber architecture for collecting and processing users' activity data, describe several different user interfaces tried with TaskTracer, and discuss the possibility of applying machine learning techniques to recognize/predict users' tasks.
tasktracker:支持多任务知识型员工的桌面环境
这篇论文报告了TaskTracer——一个软件系统,旨在帮助高度多任务的知识工作者快速定位、发现和重用他们用来成功完成任务的过去的过程。该系统监视用户与计算机的交互,收集用户活动和访问资源的详细记录,将每个交互事件与特定任务联系起来(自动或在用户的帮助下),使用户能够访问过去活动的记录并快速恢复任务上下文。我们提出了一种新的用于收集和处理用户活动数据的发布者-订阅者架构,描述了TaskTracer尝试的几种不同的用户界面,并讨论了应用机器学习技术来识别/预测用户任务的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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