کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
896425 1472400 2015 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Predicting the pattern of technology convergence using big-data technology on large-scale triadic patents
ترجمه فارسی عنوان
پیش بینی الگوی همگرایی تکنولوژی با استفاده از تکنولوژی داده های بزرگ بر روی مقیاس بزرگ اختراع ثبت شده سه گانه
کلمات کلیدی
همگرایی فن آوری؛ پیش بینی ارتباط؛ قانون رابطه؛ اطلاعات بزرگ؛ اختراع ثبت شده سه گانه؛ مدل موضوعی
موضوعات مرتبط
علوم انسانی و اجتماعی مدیریت، کسب و کار و حسابداری کسب و کار و مدیریت بین المللی
چکیده انگلیسی


• Entire triadic patents are analyzed using open-source big data technology.
• Potential future convergences among technologies are predicted by using Adamic/Adar similarity between IPC codes.
• With LDA, we found that peptides, viruses, proteins, and DNA constitute topics where convergences were predicted.

Understanding technology convergence became crucial for pursuing innovation and economic growth. This paper attempts to predict the pattern of technology convergence by jointly applying the Association Rule and Link Prediction to entire IPCs related to triadic patents filed during the period from 1955 to 2011. We further use a topic model to discover emerging areas of the predicted technology convergence. The results show that the medical area is in the center of convergence, and we predict that technologies for treating respiratory system/blood/sense disorders are associated with the technologies of genetic engineering/peptide/heterocyclic compounds. After eliminating the majority of convergence, we found the convergence pattern among activating catalysts, printing, advanced networking, controlling devices, secured communication with in-memory system, television system with pattern recognition, and image processing and analyzing technologies. The results of our study are expected to contribute to firms that seek new innovative technological domain.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Technological Forecasting and Social Change - Volume 100, November 2015, Pages 317–329
نویسندگان
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