Semantic Patent Analysis System Based on Big Data

Shin, Junghoon; Lee, Sang-Jun; Wang, Taehyung

doi:10.1109/icsc.2017.20

Cited by 4 publications

(3 citation statements)

References 3 publications

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“…Tool. In addition to the existing intellectual property information retrieval technology problems and challenges [51], data explosion in the network era, in particular patent in-depth analysis, has become a key research field for researchers or enterprises, combining with emerging science and technology and bringing new opportunities and challenges [52,53]. e following mainly introduces the limitations from three aspects: cloud platform support, data encryption and privacy protection, and ontology model building knowledge system.…”

Section: Limitation Of Present Patent Analysismentioning

confidence: 99%

A Survey on Services Provision and Distribution of Official and Commercial Intellectual Property Platforms

Wang

Gui

2020

Security and Communication Networks

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Next generation of Information Technologies (IT), such as edging/cloud computing, cybersecurity, and artificial intelligence, has been in a rapid development and therefore concerned wide areas. Management of Intellectual Property Rights (IPR) plays an increasingly important role on knowledge design and engineering, innovation and patent management, intangible assets audition, R&D, and so forth; however, it also meets the challenges from proper platform and service provision, especially when large-scale mobile and distributed requirements become popular. In this paper, Intellectual Property Platforms and corresponding commercial tools have been collected, investigated, and reviewed, involving official platforms in China, USA, EU, and another 6 countries, as well as 12 intellectual property analysis tools commonly used online. Detailed comparison and discussion have been undertaken in order to find potential challenges and opportunities for improved service provision, for example, searching privacy preservation, cloud/edge-based service offloading and efficient distribution, and ontology-based intelligent IPR engineering, which can possibly be commercialised in the near future.

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Section: Limitation Of Present Patent Analysismentioning

confidence: 99%

A Survey on Services Provision and Distribution of Official and Commercial Intellectual Property Platforms

Wang

Gui

2020

Security and Communication Networks

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“…Different types of patent data, such as bibliometric, descriptive, and citation information, have been analyzed for a broad range of purposes, including trend analysis [19], competitor analysis [19,20], and opportunity analysis [21][22][23][24]. Focusing on the semi-structured and unstructured patent data, which are gaining an increasing interest, a patent analysis system that enables to analyze such a large size of data in an efficient manner was proposed as well [25]. More recent attempts at big data analysis for technology planning have included the introduction of other available technology planning data.…”

Section: Big Data Analysis In Technology Planningmentioning

confidence: 99%

How Can Big Data Complement Expert Analysis? A Value Chain Case Study

Kim

Lee

2018

Sustainability

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Abstract:In the world of big data, there is a need to investigate how data-driven approaches can support expert-based analyses during a technology planning process. To meet this goal, we examined opportunities and challenges for big data analytics in the social sciences, particularly with respect to value chain analysis. To accomplish this, we designed a value chain mapping experiment that aimed to compare the results of expert-based and data-based mappings. In the expert-based approach, we asked an industry expert to visually depict an industry value chain based on insights and collected data. We also reviewed a previously published value chain developed by a panel of industry experts during a national technology planning process. In the data-driven analysis, we used a massive number of business transaction records between companies under the assumption that the data would be useful in identifying relationships between items in a value chain. The case study results demonstrated that data-driven analysis can help researchers understand the current status of industry structures, enabling them to develop more realistic, although less flexible value chain maps. This approach is expected to provide more value when used in combination with other databases. It is important to note that significant effort is required to develop an elaborate analysis algorithm, and data preprocessing is essential for obtaining meaningful results, both of which make this approach challenging. Experts' insights are still helpful for validating the analytic results in value chain mapping.

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“…Aunque en muchos casos las oficinas de propiedad industrial y otras empresas relacionadas declaran ofrecer servicios de búsqueda semántica de patentes, estas funcionalidades están referidas a sinonimia, variaciones de palabras u otros mecanismos, pero no apuntan a tecnologías basadas en linked data. Por otra parte, también existen desarrollos orientados hacia la combinación semántica de keywords para fortalecer los análisis de tendencias tecnológicas en patentes o sistemas de análisis semánticos basados en big data (An et al, 2018;Shin, Lee y Wang, 2017).…”

Section: Web Semántica Y Propiedad Industrialunclassified

Integración semiautomática de tecnologías de la web semántica en bases de datos de patentes

Reyes-Lillo

2018

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Se analiza la aplicación de tecnologías de la web semántica al ámbito de las patentes y se propone una estrategia metodológica de integración semiautomática de tecnologías de linked data a bases de datos relacionales de patentes. En primera instancia, se conceptualiza la documentación de patentes y su potencial integración de tecnologías de web semántica. A continuación, se analiza el modelo de datos para establecer las relaciones potenciales de la fuente de datos con una ontología del ámbito de la propiedad industrial. Posteriormente, se efectúa un mapping o una traducción de la base de datos a RDF basado en R2RML mediante Karma, un software de integración de datos. Finalmente, se describe el procedimiento de modelado de datos para la publicación de información de patentes en un modelo RDF.

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Semantic Patent Analysis System Based on Big Data

Cited by 4 publications

References 3 publications

A Survey on Services Provision and Distribution of Official and Commercial Intellectual Property Platforms

A Survey on Services Provision and Distribution of Official and Commercial Intellectual Property Platforms

How Can Big Data Complement Expert Analysis? A Value Chain Case Study

Integración semiautomática de tecnologías de la web semántica en bases de datos de patentes

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