With the development of computer network and the popularity of smart devices, the Computer Supported Collaborative Working Environment (CSCWE) greatly simplifies the traditional collaboration pattern. However, there exist a large number of collaborative interactions and related collaborative traces, which have brought a variety of new problems and challenges to the research and development of Computer Supported Collaborative Working Environment. Starting from this point, this project intends to consider taking advantage of Collaborative Trace Theory and analyzing practical cases in order to systematically study the group’s various collaborative behaviors in the Web-based Collaborative Working Environment. First, we plan on building a cross-system and cross-device Web-based Collaborative Working Environment; Second, based on Collaborative Trace Theory, we are going to construct a group Collaborative Trace Model and an exploitation framework to record every kind of collaborative behavior in the group; Third, with advanced artificial intelligence algorithms, we will develop many types of applications or tools that entirely rely on collaborative traces. In practical cases, these applications could help collaborators manage and extract different kinds of collaborative informations and improve their work efficiency. Last but not least, from the feedbacks of various practical study cases, we will adjust the Collaborative Trace Model and framework, and also improve our proposed Collaborative Working Environment. This project is conductive to promote innovation and development of Collaborative Trace Theory. Meantime, it also provides the theory basis and technology supports for solving the large cross-system cross-device complex collaborative behaviors issues and promotes the future development of Computer Supported Cooperative Work。
随着计算机网络的普及和各种智能设备的流行,计算机支持的协同工作环境日益简化了传统的协同工作方式,但面对频繁大量的协作行为及其协作痕迹,计算机协同工作环境的研究与开发面临新的问题与挑战。基于此,本项目拟考虑网络协作环境,应用协作痕迹相关理论、辅以实证分析对小组的协作行为进行系统研究。首先,拟考虑搭建跨系统、跨设备的网络协作环境;其次,基于协作痕迹理论构建小组协作痕迹模型和开发利用框架,记录小组的各种协作行为;第三,借助先进的人工智能算法开发基于协作痕迹的各类应用和工具,辅以算例挖掘提取各类协作知识,提高团队的工作效率;最后,结合实证开展不同协作场景下的跟踪与反馈分析,进一步调整协作痕迹模型,改进协作环境。本项目的研究将有利于推动协作痕迹理论的发展与创新,同时也为解决未来大规模跨系统、跨设备复杂协作行为问题提供理论依据和技术支持,从而促进计算机支持的协同工作进一步发展。
本研究项目的结果包括四方面内容:(1)协作痕迹模型和协作痕迹开发框架的研究;(2)跨平台、跨设备协作环境的研究;(3)基于协作痕迹模型和人工智能的理论和算法研究;(4)协作痕迹和协作环境应用工具的开发研究.在第一方面,基于协作痕迹理论分析了小组成员间和协作小组间的协作交互行为和协作关系,继续深入研究了更加一般化的小组协作交互模型,构建并实现了相应的协作痕迹模型和协作痕迹开发框架。.在第二方面,基于协作痕迹模型及其开发框架构建了基于CSCW协同计算系统的模型框架,阐述了框架中各主要模块的功能和模块间的交互模式;从组织行为学、心理学、社会学、动态小组等理论入手对协同工作环境中小组成员的角色和价值展开研究,构建了基于CSCW的协同小组成员价值网模型,实现了小组协作痕迹的再分析。.在第三方面,参考并对比各类组推荐算法,选取合适的人工智能理论和算法,尝试基于小组协同痕迹进行“组协作关系”推荐,并将小组协同痕迹和协作交互过程可视化。.在第四方面,在协作痕迹理论和协同工作环境研究的基础上开展协作痕迹理论的应用和开发,通过浏览器之间的交互,实现协同工作的跨平台、跨设备的目标。
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数据更新时间:2023-05-31
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