The Experts below are selected from a list of 79308 Experts worldwide ranked by ideXlab platform
Janghyeok Yoon - One of the best experts on this subject based on the ideXlab platform.
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application Technology opportunity discovery from Technology portfolios use of patent classification and collaborative filtering
Technological Forecasting and Social Change, 2017Co-Authors: Youngjin Park, Janghyeok YoonAbstract:Technology opportunity discovery (TOD), customized to a firm's current Technology capability, can be a good starting point to formulate a Technology strategy for a firm that lacks Technology information, experts, and/or facilities. Although patent-based studies have suggested systematic methods for customized TOD, these methods have limitations such as insufficient consideration of a target firm's Technology portfolio and difficulty of method reproducibility due to expert intervention-based text mining. Therefore, this paper proposes an approach to determine application Technology opportunities customized to a target firm by applying collaborative filtering to firms' Technology portfolios, which are represented as a set of patent classification codes of the firm's patents. The proposed method involves 1) structuring Technology portfolios as firm-international patent classification (IPC) distribution vectors using main group-level IPC codes of the applicants' patents, 2) recommending main group-level IPCs untapped by the target firm and with high preference scores by using collaborative filtering, and 3) classifying the recommended IPCs for the firm's strategic decision-making support using indexes of heterogeneity, growth rate, and competition level. To show the workings of this approach, we applied it to a high-tech firm with wireless communication Technology, building on the analysis of large-scale patents and their applicants. This approach is expected to contribute to the systematic identification of application Technology opportunities customized to firms and across various industries, and to become a basis for developing future Technology Intelligence systems.
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trendperceptor a property function based Technology Intelligence system for identifying Technology trends from patents
Expert Systems With Applications, 2012Co-Authors: Janghyeok Yoon, Kwangsoo KimAbstract:Abstract Technology Intelligence systems are vital components for planning of Technology development and formulation of Technology strategies. Although such systems provide computation supports for Technology analysis, much effort and intervention of experts, who may be expensive or unavailable, is required in gathering processes of information for analysis. As a remedy, this paper proposes TrendPerceptor, a system that uses a property–function based approach. The proposed system assists experts (1) to identify trends in invention concepts from patents, and (2) to perform evolution trend analysis of patents for Technology forecasting. For this purpose, a module of the system uses grammatical analysis of textual information to automatically extract properties and functions, which show innovation directions in a given Technology. Using the identified properties and functions, a module for invention concept analysis based on network analysis and a module for evolution trend analysis based on TRIZ (Russian acronym of the Theory of Inventive Problem Solving) trends are suggested. This paper describes the architecture of a system composed of these three modules, and illustrates two case studies using the system.
Tugrul U. Daim - One of the best experts on this subject based on the ideXlab platform.
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Technology Intelligence map autonomous car
2021Co-Authors: Shuying Lee, Fayez Alsoubie, Tugrul U. DaimAbstract:Autonomous vehicle Technology affects the traditional automotive industry and other related industries. However, it is much more difficult to achieve this transformation than electric car. We investigated different perspectives regarding the impact of autonomous driving through a Strengths Weaknesses Opportunities Threats (SWOT) analysis: Strength, Weakness, Opportunities, and Threats. Patent analysis and Social Network Analysis (SNA) are combined as a major tool for strategic planning to reveal the implicit R&D partnerships and explicit strategies at the company level. The case study of Google’s Autonomous Vehicle Technology shows that competitive and complementary interactions influence the formation of partnerships in the market. This study shows that SNA in a complex network setting will provide the abundant and unbiased analysis to high-quality decision-making.
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Technology Intelligence map finance machine learning
2021Co-Authors: Mohammadsaleh Saadatmand, Tugrul U. DaimAbstract:Although the terms of machine learning and deep learning have been widely used in the financial press and media, lack of agreement in the scientific and professional community about a holistic view of best practices, use cases, and trends still exists. Considering the need for filling this gap, the main aim of this study is to investigate and map the literature at the intersection of machine and deep learning as a subset, and finance and investment. This research proposes the use of bibliometric analysis of the literature that highlights the most important articles for this area of research. Specifically, this technique is applied to the literature about machine learning applications in investment and finance, resulting in a bibliographical review of the significant studies about the topic. The author evaluates papers indexed in the Scopus database. This study opens avenues for further research by concentrating on the importance of artificial Intelligence and, specifically, machine learning in investment research and practice. Additionally, this review contributes by showing scholars and investment professionals in the areas in which machine learning can add value to investment research.
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Technology roadmap development process trdp in the medical electronic device industry
International Journal of Business Innovation and Research, 2013Co-Authors: Tugrul U. Daim, Fredy Gomez, Hilary Martin, Nasir Jamil SheikhAbstract:Technology Intelligence using techniques such as data mining or patent analyses is not a new concept in the management of Technology. Nevertheless, there is a lack of useful, user-friendly techniques that incorporate quantitative data and expert judgements in Technology forecasting, especially if the application targets the medical electronic device industry. This study aims to develop a new model that integrates quantitative data from a variety of sources and expert judgements to develop a Technology roadmap for emerging technologies.
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Technology roadmap development process trdp for the service sector a conceptual framework
Technology in Society, 2012Co-Authors: Hilary Martin, Tugrul U. DaimAbstract:Abstract This paper provides a decision making framework for development of Technology roadmaps by integrating emerging Technology Intelligence with established decision making and product development methods. This paper integrates the following methods: Technology mining, analytic hierarchy process, and Technology roadmapping Specifically the emphasis is pointed towards service industry where research has indicated major differences exist when compared to the manufacturing industries. The framework is detailed in the paper providing a platform for practitioners to adopt for their own decisions to make and for researchers to expand by applying it to different service industries.
Byungun Yoon - One of the best experts on this subject based on the ideXlab platform.
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techword development of a Technology lexical database for structuring textual Technology information based on natural language processing
Expert Systems With Applications, 2021Co-Authors: Hyejin Jang, Yujin Jeong, Byungun YoonAbstract:Abstract The role of text mining based on technological documents such as patents is important in the research field of Technology Intelligence for Technology R&D planning. In addition, WordNet, an English-based lexical database, is widely used for pre-processing text data such as word lemmatization and synonym search. However, technological vocabulary information is complex and specific, and WordNet’s ability to analyze technological information is limited in its reflecting technological features. Thus, to improve the text mining performance of technological information, this study proposes a methodology for designing a TechWord-based lexical database that is based on the lexical characteristics of technological words that are differentiated from general words. To do this, we define TechWord, a Technology lexical information, and construct a TechSynset, a synonym set between TechWords. First, through dependency parsing between words, TechWord, a unit word that describes a Technology, is structured and identifies nouns and verbs. The importance of connectivity is investigated by a network centrality index analysis based on the dependency relations of words. Subsequently, to search for synonyms suitable for the target Technology domain, a TechSynset is constructed through synset information, with an additional analysis that calculates cosine similarity based on a word embedding vector. Applying the proposed methodology to the actual Technology-related information analysis, we collect patent data on the technological fields of the automotive field, and present the results of the TechWord and TechSynset. This study improves technological information-based text mining by structuring the word-to-word link information in technological documents based on an automated process.
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on the development of a Technology Intelligence tool for identifying Technology opportunity
Expert Systems With Applications, 2008Co-Authors: Byungun YoonAbstract:Technology Intelligence tools have come to be regarded as vital components in planning for Technology development and formulating Technology strategies. However, most such tools currently focus on providing graphical frameworks and databases to support the process of Technology analysis. Techpioneer, the proposed tool in this paper, aims to offer decisive information in order to identify Technology opportunities. To this end, the system uses textual information from technological document databases and applies morphology analysis to derive promising alternatives and conjoint analysis to evaluate their priority. In addition, the method used in developing a Technology dictionary is presented, employing clustering and network analysis. This system also has the ability to communicate with experts in order to estimate the value of existing patents, which is inevitable for the priority-setting of alternatives, construct a morphological matrix and so on. This paper presents the system architecture and functions of this tool and moreover, illustrates the prototype implementation and case study of the same.
Kwangsoo Kim - One of the best experts on this subject based on the ideXlab platform.
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trendperceptor a property function based Technology Intelligence system for identifying Technology trends from patents
Expert Systems With Applications, 2012Co-Authors: Janghyeok Yoon, Kwangsoo KimAbstract:Abstract Technology Intelligence systems are vital components for planning of Technology development and formulation of Technology strategies. Although such systems provide computation supports for Technology analysis, much effort and intervention of experts, who may be expensive or unavailable, is required in gathering processes of information for analysis. As a remedy, this paper proposes TrendPerceptor, a system that uses a property–function based approach. The proposed system assists experts (1) to identify trends in invention concepts from patents, and (2) to perform evolution trend analysis of patents for Technology forecasting. For this purpose, a module of the system uses grammatical analysis of textual information to automatically extract properties and functions, which show innovation directions in a given Technology. Using the identified properties and functions, a module for invention concept analysis based on network analysis and a module for evolution trend analysis based on TRIZ (Russian acronym of the Theory of Inventive Problem Solving) trends are suggested. This paper describes the architecture of a system composed of these three modules, and illustrates two case studies using the system.
Lima C.a.s. - One of the best experts on this subject based on the ideXlab platform.
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Long Range Trends In The Automobile Industry Output: Depensation Effects In The Logistic Modelling
2015Co-Authors: Miranda L.c.m., Lima C.a.s.Abstract:Automobile industry productivity has profited from incorporating Technology Intelligence (TI) methods as customers became concerned with the technological innovation contents and environmental safety of automobiles. Time series for automobile fleets accretion were analysed using a modified logistic model we recently proposed, consisting in splitting the logistic equation into a product of depensatory and compensatory components. To properly address the influence upon the per capita growth rate and occupancy index of cars fleets from those concerns, a fertility (Allee depensation effect) component is incorporated. Japanese and worldwide automobile fleets are case studies. Synergetic coupling of this methodology to TI techniques is commented upon. Copyright © 2011 Inderscience Enterprises Ltd.713353Allee, W.C., (1931) Animal Aggregations. A Study in General Sociology, , University of Chicago Press, ChicagoAllee, W.C., (1932) Animal Life and Social Growth, , University of Chicago Press, ChicagoAlso Williams & Wilkins BaltimoreBardou, J.P., Chanaron, J.J., Fridenson, P., Laux, J.M., (1982) The Automobile Revolution: The Impact of An Industry, , The North Carolina University Press, Chapel Hill, N.CBeise, M., Rennings, K., The impact of national environmental policy on the global success of next-generation automobiles (2004) International Journal of Energy Technology and Policy, 2 (3), pp. 272-283Berry, B.J.L., A pacemaker for the long wave (2000) Technological Forecasting and Social Change, 63 (1), pp. 1-23. , DOI 10.1016/S0040-1625(99)00051-7Berry, B.J.L., Kim, H., Baker, E.S., Low-frequency waves of inflation and economic growth: Digital spectral analysis (2001) Technological Forecasting and Social Change, 68 (1), pp. 63-73. , DOI 10.1016/S0040-1625(00)00119-0, PII S0040162500001190Burrows, M., Omar, M., Sustainable energy policies as a source of competitive advantage in the UK service industry (2007) World Review of Entrepreneurship, Management and Sustainable Development, 3 (3-4), pp. 231-250(2010), www.cargroup.org, CAR Center for Automotive Research Internet address Last accessed November 2010)Cusumano, M., Manufacturing innovation: Lessons from the Japanese auto industry (1988) MIT Sloan Management Review, 30 (1), pp. 29-39Fisher, J., Pry, V., A simple substitution model of technological change (1971) Technol. 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(Lond.), 40, pp. iv-viiHill, A.V., The combinations of haemoglobin with oxygen and carbon monoxide (1913) Biochemical J., 7, pp. 471-480(2009) JAMA, , www.jama-englisg.jp, Japan Automobile Manufacturers Association, Motor Vehicle Statistics of Japan 2009, Internet address: Last accessed July 2009Kanama, D., A Japanese experience of a mission-oriented multi-methodology Technology foresight process: An empirical trial of a new Technology foresight process by integration of the Delphi method and scenario (2010) International Journal of Technology Intelligence and Planning, 6 (3), pp. 253-267Kerr, C.I.V., Mortara, L., Phaal, R., Probert, D.R., A conceptual model for Technology Intelligence (2006) International Journal of Technology Intelligence and Planning, 2 (1), pp. 73-93Lichtenthaler, E., Technological change and the Technology Intelligence process: A case study (2004) Journal of Engineering and Technology Management, 21 (4), pp. 331-348Lichtenthaler, E., The choice of Technology Intelligence methods in multinationals: Towards a contingency approach (2005) International Journal of Technology Management, 32 (3-4), pp. 388-407Maddison, A., (2003) The World Economy: Historical Statistics, , http://www.ggdc.net/maddison/, OECD Publishing, Paris, The GDP and population data over the 1-2003 AD period, for various countries, can be accessed at the website Last accessed March 2009Marchetti, C., Society as a learning system: Discovery, invention and innovations cycles revisited (1980) Technol. Forecast. Soc. Change, 18, pp. 257-282Marchetti, C., Fifty years pulsation in human affairs (1986) Futures, 17, pp. 376-388Metcalfe, J.S., Institutions and progress (2001) Industrial and Corporate Change, 10 (3), pp. 561-586Meyer, P.S., Bi-logistic growth (1994) Technol. Forecast. Soc. Change, 47, pp. 89-102Miranda, L.C.M., Lima, C.A.S., A new methodology for the logistic analysis of evolutionary S-shaped processes: Application to historical time series and forecasting (2010) Technol. Forecast Soc. Change, 77 (2), pp. 175-192Miranda, L.C.M., Lima, C.A.S., On the logistic modeling and forecasting of evolutionary processes: Application to human population dynamics (2010) Technol. Forecast. Soc. Change, 77 (5), pp. 699-711Miranda, L.C.M., Lima, C.A.S., On trends and rhythms in scientific and technological knowledge evolution: A quantitative analysis', Int (2010) J. 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On Trends And Rhythms In Scientific And Technological Knowledge Evolution: A Quantitative Analysis
'Inderscience Publishers', 2015Co-Authors: Miranda L.c.m., Lima C.a.s.Abstract:The evolutionary character of science and Technology and their social implications are tracked down by studying five centuries long time series encompassing both the most impacting published scientific works and recorded technological inventions and a 125 years long time series of major granted patents. Using a novel procedure (Miranda and Lima, 2010a, 2010b), typical Kuznets economic cycles (15-25 years) are shown to be modulating the multi-logistic modelling-to-data corresponding residuals series, suggesting that changes and investments in infrastructure are essential driving motors for the observed data. Amidst a complex of components, knowledge evolution emerges as a major one in providing the overall force that catalyses the ensuing basic socially impacting changes. Our results are also discussed under the views of a world system theoretical framework where knowledge evolution, technological Intelligence and innovation join together into a feedback system that influenced decision-making towards socio-economic policies that enhanced human welfare evolution throughout centuries. Copyright © 2010 Inderscience Enterprises Ltd.6176109(2006) Delay Differential Equations and Applications, , Arino, O., Hbid, M.L. and Ait Dads, E. (Eds.), Springer-Verlag, Doordrecht(1992) Shaping Technology/Building Society - Studies in Sociotechnical Change, , Bijker, W.E. and Law, J. (Eds.), The MIT Press, Cambridge(1987) The Social Construction of Technological Systems - New Directions in the Sociology and History of Technology, , Bijker, W.E., Hughes, T.P. and Pinch, T.J. (Eds.), The MIT Press, CambridgeChurch, A.J., A bibliography of symbolic logic (1936) J. 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