首页> 外文会议>Semantic methods for knowledge management and communication >Using IPC-Based Clustering and Link Analysis to Observe the Technological Directions
【24h】

Using IPC-Based Clustering and Link Analysis to Observe the Technological Directions

机译:使用基于IPC的聚类和链接分析来遵守技术方向

获取原文
获取原文并翻译 | 示例

摘要

To explore the technological directions of an industry is essential for companies and stakeholders to anticipate the future situations and R&D activities. Patent data contains plentiful technical information, which is appropriate to be used in technological analysis in order to find out the technical topics and possible directions. Due to the complex nature of patent data, two data mining methods: IPC-based clustering and link analysis, are used to figure out the potential tendencies on thin-film solar cell. An IPC-based clustering algorithm will be proposed and utilized to generate the significant categories via the IPC and Abstract fields, while the link analysis will be adopted to draw a link diagram for the whole dataset via the Abstract, Issue Date, and Assignee Country fields. During experiment, the technical categories will be identified using the IPC-based clustering, and the technological directions will be found through the link analysis. Finally, the recognized technical categories and technological directions will be provided to the managers and stakeholders for assisting their decision making.
机译:探索行业的技术方向对于公司和利益相关者预测未来情况和研发活动至关重要。专利数据包含大量技术信息,这些信息适合用于技术分析,以便找到技术主题和可能的方向。由于专利数据的复杂性,使用两种数据挖掘方法:基于IPC的聚类和链接分析来确定薄膜太阳能电池的潜在趋势。将提出一种基于IPC的聚类算法,并将其用于通过IPC和“摘要”字段生成重要类别,同时将采用链接分析通过“摘要”,“发行日期”和“受让人国家”字段绘制整个数据集的链接图。 。在实验过程中,将使用基于IPC的聚类来识别技术类别,并通过链接分析找到技术方向。最后,将公认的技术类别和技术指导提供给管理者和利益相关者,以帮助他们进行决策。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号