The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approaches
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...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
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Cambridge University Press
2017-01-01
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Series: | Design Science |
Subjects: | |
Online Access: | https://www.cambridge.org/core/product/identifier/S2053470117000191/type/journal_article |
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author | Andrew Wodehouse Gokula Vasantha Jonathan Corney Ross Maclachlan Ananda Jagadeesan |
author_facet | Andrew Wodehouse Gokula Vasantha Jonathan Corney Ross Maclachlan Ananda Jagadeesan |
author_sort | Andrew Wodehouse |
collection | DOAJ |
description | 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. |
first_indexed | 2024-04-10T04:51:53Z |
format | Article |
id | doaj.art-ba046c04befa4c85984e7b8f11892c6a |
institution | Directory Open Access Journal |
issn | 2053-4701 |
language | English |
last_indexed | 2024-04-10T04:51:53Z |
publishDate | 2017-01-01 |
publisher | Cambridge University Press |
record_format | Article |
series | Design Science |
spelling | doaj.art-ba046c04befa4c85984e7b8f11892c6a2023-03-09T12:31:57ZengCambridge University PressDesign Science2053-47012017-01-01310.1017/dsj.2017.19The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approachesAndrew WodehouseGokula VasanthaJonathan CorneyRoss MaclachlanAnanda JagadeesanThis 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.https://www.cambridge.org/core/product/identifier/S2053470117000191/type/journal_articlepatentsdesign knowledgeinformation processingcrowdsourcingdesign process |
spellingShingle | Andrew Wodehouse Gokula Vasantha Jonathan Corney Ross Maclachlan Ananda Jagadeesan The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approaches Design Science patents design knowledge information processing crowdsourcing design process |
title | The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approaches |
title_full | The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approaches |
title_fullStr | The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approaches |
title_full_unstemmed | The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approaches |
title_short | The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approaches |
title_sort | generation of problem focussed patent clusters a comparative analysis of crowd intelligence with algorithmic and expert approaches |
topic | patents design knowledge information processing crowdsourcing design process |
url | https://www.cambridge.org/core/product/identifier/S2053470117000191/type/journal_article |
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