开放式团队创新研讨主题识别方法及其可视化

Topic Identification and Visualization for Open Team Innovation Argumentation

当前全球创新方向正在向开放式团队创新转变。开放式团队创新环境中,基于网络的电子研讨成为最基本、最重要的创新活动,及时准确地识别海量电子研讨信息的研讨主题,并通过可视化形象地展示给创新团队成员,对提高开放式团队创新的效率和质量至关重要。针对传统主题挖掘研究中存在的主要问题,提出了开放式团队创新研讨主题识别方法。该方法在文档建模阶段提出并建立了基于团队创新研讨信息本体和研讨树结构的研讨文本语义计算方法;在研讨主题聚类阶段,针对开放式团队创新研讨的短文本特征,运用AntSA算法对研讨文本进行聚类分析;并通过计算聚类结果中每个节点名词的研讨主题标签贡献率,识别每个类别的研讨主题。最后,根据所提出的开放式团队创新研讨主题识别方法,设计和开发了开放式团队创新研讨主题可视化系统,识别并直观显示各研讨主题间的语义关系和结构关系,并对其进行了实验研究。

The global innovation landscape is changing open innovation. In open innovative team, electronic argumentation based on Web is becoming one of the most primary and important innovative activities. It is very important to mine, identify and visualize the argumentation topic of mass argumentation information in the process of open team innovation. These benefit not only mastering the whole team progress and the latest development rapidly and accurately, but also recommending appropriate knowledge and field experts to team members according to their argumentation topics. In order to strike on the main problems of classic text topic mining, an automatic topic identification method is studied and proposed in this paper. A semantic computing method based on argumentation ontology and argumentation tree structure is proposed and built during documentation modeling phase. AntSA algorithm is employed for short-text clustering during topic mining phase. The contribution ratio of the nouns in each category node to argumentation topics is proposed and computed to identify topics of each category. Consequently, the visualization system of topic identification for open team innovation argumentation is designed and development based on the proposed method. The visualization system is able to automatically identify and intuitively exhibit semantic relationships and structural relationships between various argumentation topics. Experiment study of topic identification method for open team innovation argumentation is conducted as well.