Patent Big Data Analysis using Fuzzy Learning

Park, Sangsung; Lee, Seung-Joo; Jun, Sunghae

doi:10.1007/s40815-016-0192-y

Cited by 24 publications

(18 citation statements)

References 19 publications

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“…Gray theory has good applicability in the solution of uncertainty problems. Gray clustering is a data mining method for classifying unclear data systems, which has been widely used in the era of big data [20,21]. Highway landslides are affected by many factors; meanwhile, these factors are closely connected.…”

Section: Gray Clustering Disaster Assessment Methods Based Onmentioning

confidence: 99%

[Retracted] Integration and Fusion of Geologic Hazard Data under Deep Learning and Big Data Analysis Technology

Liu

2021

Complexity

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To discuss the analysis and evaluation of highway landslides, the application of data mining methods combined with deep learning frameworks in geologic hazard evaluation and monitoring is explored preliminarily. On the premise of optimizing the processing of landslide images, first, the Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) based on the natural statistical characteristics of the spatial domain is introduced, which is initially combined with Super-Resolution Convolutional Neural Network (SRCNN). Then, the AlexNet is fine-tuned and applied to highway landslide monitoring and surveying. Finally, an entropy weight gray clustering evaluation method based on data mining analysis is proposed, and the performances of several methods are verified. The results show that the average score of the BRISQUE algorithm in Image Quality Assessment (IQA) is above 0.9, and the average running time is 0.1523 s. The combination of BRISQUE and SRCNN can improve the image quality significantly. After fine-tuning, the recognition accuracy of AlexNet for landslide images can reach about 80%. The evaluation method based on gray clustering can effectively determine the correlation between soil moisture content and slope angle and thereby be applied to the analysis and evaluation of highway landslides. The results are beneficial to the judgment and assessment of highway landslide conditions, which can be extended to research on other geologic hazards.

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Section: Gray Clustering Disaster Assessment Methods Based Onmentioning

confidence: 99%

[Retracted] Integration and Fusion of Geologic Hazard Data under Deep Learning and Big Data Analysis Technology

Liu

2021

Complexity

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“…We believe that big data analytics can be used for collecting, transforming, and analyzing different types of raw data about international technological collaboration. For instance, more technological information could be available from patent data by big data analytics [77]. This is our key research direction for the future.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Exploring the Technological Collaboration Characteristics of the Global Integrated Circuit Manufacturing Industry

et al. 2018

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Abstract:With the intensification of international competition, there are many international technological collaborations in the integrated circuit manufacturing (ICM) industry. The importance of improving the level of international technological collaboration is becoming more and more prominent. Therefore, it is vital for a country, a region, or an institution to understand the international technological collaboration characteristics of the ICM industry and, thus, to know how to enhance its own international technological collaboration. This paper depicts the international technological collaboration characteristics of the ICM industry based on patent analysis. Four aspects, which include collaboration patterns, collaboration networks, collaboration institutions, and collaboration impacts, are analyzed by utilizing patent association analysis and social network analysis. The findings include the following: first, in regard to international technological collaboration, the USA has the highest level, while Germany has great potential for future development; second, Asia and Europe have already formed clusters, respectively, in the cooperative network; last, but not least, research institutions, colleges, and universities should also actively participate in international collaboration. In general, this study provides an objective reference for policy making, competitiveness, and sustainability in the ICM industry. The framework presented in this paper could be applied to examine other industrial international technological collaborations.

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“…Park vd. [35] tarafından yapılan bu alandaki bir çalışmada 3 boyutlu yazıcı teknolojisine sahip 2583 patent üzerinde metin madenciliği yoluyla patent-anahtar kelime matrisleri oluşturulmuş, bu anahtar kelimeler kullanılarak kural tabanlı bulanık modeller oluşturulmuştur. Bulanık sınıflandırma yolu ile patentler benzer gruplara ayrılmış, bulanık regresyon ile patent anahtar kelimeleri arasında teknolojik ilişkiler çıkarılmış ve bulanık kümeleme yolu ile teknolojik alanlar kümelenmiştir.…”

Section: E Patentlerin Teknolojik Analizi Ile Stratejik Teknoloji Yöunclassified

Patent Mining

Kayakökü

Akay

2021

Politeknik Dergisi

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Patent veri tabanları sürekli ve süratli bir şekilde büyüyen hacmiyle, günümüzün en önemli teknik bilgi kaynağı konumundadır. Oldukça geniş ve detaylı olan patent veri tabanlarından bilgi elde edebilmek için, gelişen veri analiz yöntemlerine başvurmak kaçınılmaz hale gelmiştir. Patent verisinden bilgi elde etmeyi ifade etmek üzere son zamanlarda patent madenciliği tabiri kullanılmaya başlanmıştır. Patent veri tabanlarının hem yapısal hem de yapısal olmayan karakteri sebebiyle, patent madenciliğinde veri madenciliği tekniklerine de metin madenciliği tekniklerine de ihtiyaç duyulmaktadır. Ancak patent dokümanları buluşların teknik yönlerinin açıklandığı metinlerden oluştuğundan, metin madenciliği uygulamalarının bu alandaki işlevi daha fazladır. Bu çalışmada patent dokümanlarının özelliklerinden bahsedilerek, metin madenciliği ile elde edilebilecek sonuçlara değinilmiştir. Literatürde patent metinleri üzerinde kullanılan metin madenciliği yöntemlerinden örnekler verilmiş ve gelecekte yapılacak çalışmalara yön vermek açısından patent dokümanları arasında benzerlik tespitinin neden önemli olduğu açıklanmıştır.

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Patent Big Data Analysis using Fuzzy Learning

Cited by 24 publications

References 19 publications

[Retracted] Integration and Fusion of Geologic Hazard Data under Deep Learning and Big Data Analysis Technology

[Retracted] Integration and Fusion of Geologic Hazard Data under Deep Learning and Big Data Analysis Technology

Exploring the Technological Collaboration Characteristics of the Global Integrated Circuit Manufacturing Industry

Patent Mining

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