首页> 外文会议>IEEE International Conference on Big Data and Smart Computing >Prior Art Search Using Multi-modal Embedding of Patent Documents
【24h】

Prior Art Search Using Multi-modal Embedding of Patent Documents

机译:使用专利文件的多模式嵌入的现有技术搜索

获取原文

摘要

Due to the limitations of the existing prior art search methods, a new patent search paradigm can be innovated by the concepts based on a precise patent document embedding, and a real-time feedback. These concepts can be achieved by the following ideas. The latest language model BERT can be incorporated with the description drawing embedding so that the explorable user interactive model can be adopted to the patent domain for “Building an artificial intelligent patent search system." Therefore, these methodologies mainly with the help of deep learning can solve the traditional labor-intensive and time-consuming prior art search.
机译:由于现有的现有技术搜索方法的局限性,可以通过基于精确的专利文档嵌入和实时反馈的概念来创新新的专利搜索范例。这些概念可以通过以下思想来实现。最新的语言模型BERT可与描述图嵌入结合使用,以便可探索的用户交互模型可用于专利领域以“构建人工智能专利检索系统”。因此,这些方法主要是借助深度学习来实现的。解决了传统的劳动密集且费时的现有技术搜索。

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