The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approaches

The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approaches
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以问题为中心的专利集群的生成:群体智能与算法和专家方法的比较分析

DOI:
10.1017/dsj.2017.19
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发表时间:
2017
期刊:
影响因子:
2.4
通讯作者:
Wodehouse A
Wodehouse A
中科院分区:
--
文献类型:
--
作者:
Wodehouse A

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本文提出了一种新的众包方法来构建专利集群,并系统地将其与以前的专家和算法方法进行比较。专利数据库应该是丰富的灵感来源,可以引导工程设计师为创造性问题找到新颖的解决方案。然而,专利信息的庞大数量和复杂性意味着这种潜力很少被实现。设计人员需要的工具不是商业系统中常见的关键字驱动搜索,而是可以帮助他们在正在考虑的问题的背景下理解专利的工具。本文提出了一种解决这一问题的方法,即利用群体智能以更低的成本和更合理的方式有效生成专利集群。我们进行了一项系统研究,将人群与专家专利集群和算法专利集群的效率进行比较,结果表明,人群能够以适当的理由创建多 80% 的专利对。
This paper presents a new crowdsourcing approach to the construction of patent clusters, and systematically benchmarks it against previous expert and algorithmic approaches. Patent databases should be rich sources of inspiration which could lead engineering designers to novel solutions for creative problems. However, the sheer volume and complexity of patent information means that this potential is rarely realised. Rather than the keyword driven searches common in commercial systems, designers need tools that help them to understand patents in the context of the problem they are considering. This paper presents an approach to address this problem by using crowd intelligence for effective generation of patent clusters at lower cost and with greater rationale. A systematic study was carried out to compare the crowd’s efficiency with both expert and algorithmic patent clusters, with the results indicating that the crowd was able to create 80% more patent pairs with appropriate rationale.
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