你的公司的下一个技术是什么？机器学习和基于网络的算法之间的比较
Which will be your firm's next technology? Comparison between machine learning and network-based algorithms
摘要：
我们通过跟踪大约20万家公司十年的专利活动，重建了它们的创新动态。我们将这些公司的技术组合定义为它们提交的专利中存在的技术部门的集合。通过假设公司更频繁地转向相关领域，我们利用他们过去的活动来构建基于网络的机器学习算法，以预测未来新领域的专利提交。我们比较了不同的评估指标和预测方法，表明基于树的机器学习算法优于基于同现网络的标准方法。公司和决策者可运用这一方法，在现有创新活动的情况下，将可行的技术部门与现有创新活动无法触及的技术部门区分开来。
英文摘要：
We reconstruct the innovation dynamics of about two hundred thousand companies by following their patenting activity for about ten years. We define the technological portfolios of these companies as the set of the technological sectors present in the patents they submit. By assuming that companies move more frequently towards related sectors, we leverage on their past activity to build network-based and machine learning algorithms to forecast the future submission of patents in new sectors. We compare different evaluation metrics and prediction methodologies, showing that tree-based machine learning algorithms overperform the standard methods based on networks of co-occurrences. This methodology can be applied by firms and policymakers to disentangle, given the present innovation activity, the feasible technological sectors from those that are out of reach, given their present innovation activity.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
