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Toward incorporating a task-stage identification technique into the long-term document support process

机译:旨在将任务阶段识别技术纳入长期文档支持流程

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摘要

Effective knowledge management in a knowledge-intensive environment can place heavy demands on the information filtering (IF) strategies used to model workers' long-term task-needs. Because of the growing complexity of knowledge-intensive work tasks, a profiling technique is needed to deliver task-relevant documents to workers. In this study, we propose an IF technique with task-stage identification that provides effective codification-based support throughout the execution of a task. Task-needs pattern similarity analysis based on a correlation value is used to identify a worker's task-stage (the pre-focus, focus formulation, or post-focus task-stage). The identified task-stage is then incorporated into a profile adaptation process to generate the worker's current task profile. The results of a pilot study conducted in a research institute confirm that there is a low or negative correlation between search sessions and transactions in the pre-focus task-stage, whereas there is at least a moderate correlation between search sessions/transactions in the post-focus stage. Compared with the traditional IF technique, the proposed IF technique with task-stage identification achieves, on average, a 19.49% improvement in task-relevant document support. The results confirm the effectiveness of the proposed method for knowledge-intensive work tasks.
机译:在知识密集型环境中进行有效的知识管理可能对用于模拟工人的长期任务需求的信息过滤(IF)策略提出很高的要求。由于知识密集型工作任务的日益复杂性,需要一种配置文件技术将与任务相关的文档传递给工人。在这项研究中,我们提出了一种具有任务阶段标识的IF技术,该技术在整个任务执行过程中提供了有效的基于编码的支持。基于相关值的任务需求模式相似性分析用于识别工人的任务阶段(集中前,集中制定或集中后任务阶段)。然后,将确定的任务阶段合并到配置文件适应过程中,以生成工作人员的当前任务配置文件。在研究机构中进行的一项初步研究的结果证实,在焦点前任务阶段,搜索会话与交易之间的相关性较低或为负,而帖子中搜索会话/交易之间的相关性至少为中等焦点阶段。与传统的IF技术相比,提出的具有任务阶段标识的IF技术平均可在与任务相关的文档支持方面提高19.49%。结果证实了该方法对知识密集型工作任务的有效性。

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