...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>The Science of the Total Environment >Innovation hotspots in food waste treatment, biogas, and anaerobic digestion technology: A natural language processing approach
【24h】

Innovation hotspots in food waste treatment, biogas, and anaerobic digestion technology: A natural language processing approach

机译：食品废物处理，沼气和厌氧消化技术创新热点：一种自然语言处理方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The objective of this study is to apply natural language processing to identifying innovative technology trends related to food waste treatment, biogas, and anaerobic digestion. The methodology used involved analyzing large volumes of text data mined from 3186 patents related to these three fields. Latent Dirichlet Allocation and the perplexity method were used to identify the main topics which the patent corpora were comprised of and which technological concepts were most associated with each topic. In addition, term frequency-inverse document frequency (TI-IDF) was used to gauge the "emergingness" of certain technical concepts CTOSS the patent corpora in various years. The key results were as follows: (1) perplexity computations showed that a 20 topic models were feasible for these patent corpora; (2) topics were identified, providing an accurate picture of the patenting landscape in the analyzed fields; (3) TI-IDF analysis on unigrams, bigrams, and trigrams, supplemented with network graph analysis, revealed emerging technology trends in each year. This study has important implications for governments who need to decide where to invest resources in anaerobic food waste treatment. (C) 2019 Published by Elsevier B.V.
机译：本研究的目的是应用自然语言处理，以确定与食物废物处理，沼气和厌氧消化相关的创新技术趋势。使用的方法涉及分析大量的文本数据，从与这三个领域的3186个专利开采。潜在的Dirichlet分配和困惑方法用于识别专利组织组成的主要话题，以及哪些技术概念与每个主题最相关。此外，术语频率 - 逆文档频率（TI-IDF）用于衡量各个年度专利对象的某些技术概念的“新兴”。关键结果如下：（1）困惑计算显示，这些专利集团的20个主题模型是可行的; （2）识别主题，在分析的领域提供精确的专利景观图片; （3）UNIGRAMS，BIGRAMS和TRIGRAM的TI-IDF分析，补充了网络图分析，揭示了每年的新兴技术趋势。本研究对需要决定在厌氧食物废物处理中投资资源的地方的政府具有重要意义。 （c）2019年由elestvier b.v发布。

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