从数据堆砌到可消化片段：面向沟通的溯源日志自动分割与摘要
From Data Dump to Digestible Chunks: Automated Segmentation and Summarization of Provenance Logs for Communication
AI总结：
本文面向情报分析协作沟通，提出将交互溯源日志自动分割并生成文本卡片的摘要流水线，经多类数据集和美国国防部专家评审验证有效。
摘要：
在复杂分析会话中传达个人的意义建构过程以解释思维过程十分困难，然而大多数情报工作都发生在协作环境中。团队成员需要更深入地理解同事和下属正在完成的工作，但鲜有研究完整阐明面向分析溯源消费者的最佳实践。本研究提出一种自动摘要技术，可将分析会话切分，并把交互溯源总结为文本简介，从而支持对已完成工作进行元分析。聚焦情报分析领域，我们使用五个数据集（包括公开可用和涉密的交互日志）演示了该分割技术。我们将演示分享给一群极难接触到的专家评审人员，他们具有担任美国国防部分析师的经验。研究结果表明，所提出的流水线能够有效生成展示交互日志中关键事件的卡片，从而促进分析进展的共享。然而，我们也了解到，需要更突出的理由说明和模式引出控制，以更有效地传达分析摘要。专家评审凸显了自动化方法在应对复杂领域中溯源信息挑战方面的潜力。我们希望强调，有必要进一步研究其他领域中的溯源沟通。本文免费版本及所有补充材料可在 https://osf.io/j4bxt 获取。
英文摘要：
Communicating one's sensemaking during a complex analysis session to explain thought processes is hard, yet most intelligence occurs in collaborative settings. Team members require a deeper understanding of the work being completed by their peers and subordinates, but little research has fully articulated best practices for analytic provenance consumers. This work proposes an automatic summarization technique that separates an analysis session and summarizes interaction provenance as textual blurbs to allow for meta-analysis of work done. Focusing on the domain of intelligence analysis, we demonstrate our segmentation technique using five datasets, including both publicly available and classified interaction logs. We shared our demonstration with a notoriously inaccessible population of expert reviewers with experience as United States Department of Defense analysts. Our findings indicate that the proposed pipeline effectively generates cards that display key events from interaction logs, facilitating the sharing of analysis progress. Yet, we also hear that there is a need for more prominent justifications and pattern elicitation controls to communicate analysis summaries more effectively. The expert review highlights the potential of automated approaches in addressing the challenges of provenance information in complex domains. We'd like to emphasize the need for further research into provenance communication in other domains. A free copy of this paper and all supplemental materials are available at https://osf.io/j4bxt
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
