کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
388521 660926 2011 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Identifying core technologies based on technological cross-impacts: An association rule mining (ARM) and analytic network process (ANP) approach
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Identifying core technologies based on technological cross-impacts: An association rule mining (ARM) and analytic network process (ANP) approach
چکیده انگلیسی

This study proposes a new approach to identifying core technologies from a perspective of technological cross-impacts based on patent co-classification information with consideration of the overall interrelationships among technologies. The proposed approach is comprised of two methods: association rule mining (ARM) and the analytic network process (ANP). Firstly association rule mining (ARM) is employed to calculate the technological cross-impact indexes. Since the confidence measure in ARM is defined as a conditional probability between two technologies, it is adopted as an index for evaluating technological cross-impacts. The technological cross-impact matrix is then constructed with all calculated cross-impact indexes. Secondly, the ANP, which is a generalization of the analytic hierarchy process (AHP), is conducted to produce priorities of technologies with consideration of their direct and indirect impacts. The proposed approach can be utilized for technology monitoring for both technology planning of firms and innovation policy making of governments. A case of telecommunication technology is presented to illustrate the proposed approach.


► This study proposes a new approach to identification of core technologies from the perspectives of technological cross-impacts.
► Patent co-classification information is employed to measure technological cross-impacts.
► Association rule mining (ARM) and analytic network process (ANP) are employed to capture interrelationships among technologies.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 38, Issue 10, 15 September 2011, Pages 12559–12564
نویسندگان
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