دانلود رایگان مقاله نظارت بر فناوری در حال ظهور برنامه ریزی فناوری با کلمه کلیدی فنی

عنوان فارسی
نظارت بر فناوری های در حال ظهور برای برنامه ریزی فناوری با استفاده از کلمه کلیدی فنی مبتنی بر تجزیه و تحلیل داده های دارای حق انحصاری
عنوان انگلیسی
Monitoring emerging technologies for technology planning using technical keyword based analysis from patent data
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
12
سال انتشار
2016
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E4637
رشته های مرتبط با این مقاله
مدیریت
گرایش های مرتبط با این مقاله
مدیریت تکنولوژی و مدیریت فناوری اطلاعات
مجله
پیش بینی فنی و تغییر اجتماعی - Technological Forecasting & Social Change
دانشگاه
گروه مهندسی صنایع و مدیریت، دانشگاه علم و صنعت، کره
کلمات کلیدی
تجزیه و تحلیل ثبت اختراع، مدل مبتنی بر کلید واژه، کلید واژه فنی، برنامه ریزی فناوری
چکیده

abstract


This paper proposes technical keyword-based analysis of patents to monitor emerging technologies, and uses a keyword-based model in contents-based patent analysis. This study also presents methods to automatically select keywords and to identify the relatedness among them. After using text-mining tools and techniques to identify technical keywords, a technical keyword-context matrix is constructed. The relatedness between pairs of keywords is then identified in a transformation of this matrix. Patent documents are clustered by using a hierarchical clustering algorithm based on patent document vectors. As a result, emerging technologies can be monitored by identifying clusters composed of technical keywords. A case study of mechanisms of electron transfer in electrochemical glucose biosensors is given to demonstrate how the proposed method can monitor emerging technologies.

نتیجه گیری

5. Conclusion


This paper presents an approach to identify emerging technologies, and applied it to a case of mechanisms of electron transfer in electrochemical glucose biosensors. The proposed method uses advanced algorithms to automatically select keywords by applying a TF-IDF function, and to quantify relatedness between pairs of keywords, rather relying on domain experts as did previous keyword-based patent analysis. The algorithm to automatically select keywords replaces previous subjective judgments of domain experts with decision of high rank based on TF-IDF value, and contributes to reduction of domain experts' work by just choosing a cutoff of TF-IDF values. The algorithm to quantify relatedness provides objective evidence for keyword relatedness by identifying pairs of keywords that have high similarity values, and improves semantic processing to compare patent documents. Due to the complexity and fusion of emerging technology, two or three principal keywords are not sufficient to characterize this technology. For example,glucose biosensors entail biotechnology, electronics, and nanotechnology, so emerging technologies could not be expressed using two or three main keywords. For this reason, automatic technical keyword selection that conveys contents of patent is useful, and the relatedness between keywords database allows semantic processing of the similarity of patent documents. Consequently, our algorithms are expected to enhance reliable and objective keyword-based patent analysis to identify emerging technologies.


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