Identifying technological opportunities using the novelty detection technique: a case of laser technology in semiconductor manufacturing

While identification of technological opportunities has received considerable attention, previous studies have some weaknesses in terms of subjectivity when finding the opportunities in practical terms. This paper proposes a systematic framework to identify technological opportunities, focusing on objective evidences which are specific and practical to be used in a business environment. To do this, we used patents as a source and employed a novelty detection technique whose primary object is detecting the novel pattern. To begin with, the patents are collected from the United States Patent and Trademark Office (USPTO) database. These patents are then pre-processed into a structured keyword vector that can represent the characteristics of each patent. These keyword vectors are then used to analyse the new and emerging pattern, using the novelty detection technique. As the final step, the results are analysed to identify the technological opportunities. A case study on laser technology in lithography is presented to show the proposed framework.

[1]  William M. Pottenger,et al.  Methodologies for Trend Detection in Textual Data Mining , 2005 .

[2]  Charles R. Farrar,et al.  Novelty detection under changing environmental conditions , 2001, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[3]  Lionel Tarassenko,et al.  The use of novelty detection techniques for monitoring high-integrity plant , 2002, Proceedings of the International Conference on Control Applications.

[4]  So Young Sohn,et al.  Technology scoring model for reflecting evaluator's perception within confidence limits , 2008, Eur. J. Oper. Res..

[5]  Darrell L. Mann,et al.  Better technology forecasting using systematic innovation methods , 2003 .

[6]  Byungun Yoon,et al.  A text-mining-based patent network: Analytical tool for high-technology trend , 2004 .

[7]  Sung-Hyon Myaeng,et al.  Automatic discovery of technology trends from patent text , 2009, SAC '09.

[8]  Judith Scott Clayton,et al.  The Future , 2001, Nature.

[9]  Nils C. Newman,et al.  Measuring national ‘emerging technology’ capabilities , 2002 .

[10]  Yuh-Wen Chen,et al.  Using AHP in patent valuation , 2007, Math. Comput. Model..

[11]  Derek Barker,et al.  Technology foresight using roadmaps , 1995 .

[12]  Dipankar Dasgupta,et al.  A comparison of negative and positive selection algorithms in novel pattern detection , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[13]  Dominique R. Jolly,et al.  The issue of weightings in technology portfolio management , 2003 .

[14]  Sameer Singh,et al.  Novelty detection: a review - part 1: statistical approaches , 2003, Signal Process..

[15]  Fabrizio Sebastiani,et al.  A Tutorial on Automated Text Categorisation , 2000 .

[16]  Ola Olsson,et al.  Technological Opportunity and Growth , 2005 .

[17]  A. Jaffe.  Technological Opportunity and Spillovers of R&D: Evidence from Firms&Apos; Patents, Profits and Market Value , 1986 .

[18]  David L. Olson,et al.  Advanced Data Mining Techniques , 2008 .

[19]  William M. Pottenger,et al.  A Survey of Emerging Trend Detection in Textual Data Mining , 2004 .

[20]  Yonatan Aumann,et al.  Knowledge Management: A Text Mining Approach , 1998, PAKM.

[21]  Yongtae Park,et al.  A new method for technology valuation in monetary value: procedure and application , 2004 .

[22]  Byungun Yoon,et al.  A systematic approach for identifying technology opportunities: Keyword-based morphology analysis , 2005 .

[23]  John J. McGonagle.  Keeping abreast of science and technology: Technical intelligence for business , 1997 .

[24]  Symeon Papavassiliou,et al.  Network intrusion and fault detection: a statistical anomaly approach , 2002, IEEE Commun. Mag..

[25]  Sungjoo Lee,et al.  An approach to discovering new technology opportunities: Keyword-based patent map approach , 2009 .

[26]  Anna Nosella,et al.  Technological change and technology monitoring process: Evidence from four Italian case studies , 2008 .

[27]  Thorsten Teichert,et al.  Text mining for technology monitoring , 2002, IEEE International Engineering Management Conference.

[28]  Joseph P. Martino,et al.  Technological Forecasting---An Overview , 1980 .

[29]  Michael Gamon.  Graph-Based Text Representation for Novelty Detection , 2006 .

[30]  S. Triest,et al.  Valuing patents on cost-reducing technology: A case study , 2007 .

[31]  Alan L. Porter,et al.  Technology opportunities analysis , 1995 .

[32]  Alan L. Porter,et al.  Emerging technologies: quantitative identification and measurement , 2010, Technol. Anal. Strateg. Manag..

[33]  Alan L. Porter,et al.  Automated extraction and visualization of information for technological intelligence and forecasting , 2002 .

[34]  Kirsten Frandsen,et al.  In a Different Game , 2013 .

[35]  Byungun Yoon,et al.  On the development of a technology intelligence tool for identifying technology opportunity , 2008, Expert Syst. Appl..

[36]  Wook-Hyun Shin,et al.  Trend Properties and a Ranking Method for Automatic Trend Analysis , 2009 .

[37]  Mary Ellen Mogee,et al.  Using Patent Data for Technology Analysis and Planning , 1991 .

[38]  M. Reitzig.  What determines patent value?: Insights from the semiconductor industry , 2003 .

[39]  Ronald N. Kostoff,et al.  Science and technology roadmaps , 2001, IEEE Trans. Engineering Management.

[40]  Lionel Tarassenko,et al.  Novelty detection for the identification of abnormalities , 2000, Int. J. Syst. Sci..

[41]  K. Pavitt.  What We Know about the Strategic Management of Technology , 1990 .

[42]  V K Gupta,et al.  Carbon nanotubes: bibliometric analysis of patents , 2000 .

[43]  Fabio A. González,et al.  An Intelligent Decision Support System for Intrusion Detection and Response , 2001, MMM-ACNS.

[44]  Robert P. W. Duin,et al.  Outlier Detection Using Classifier Instability , 1998, SSPR/SPR.

[45]  Pan-Jun Kim,et al.  A Study on Updating the Knowledge Structure Using New Topic Detection Methods , 2005 .

[46]  Alan L. Porter,et al.  On the Future of Technological Forecasting , 2001 .

[47]  J. D. T. Tannock,et al.  On-line control chart pattern detection and discrimination - a neural network approach , 1999, Artif. Intell. Eng..

[48]  Yongtae Park,et al.  On the Development and Application of a Self-Organizing Feature Map-Based Patent Map , 2002 .

[49]  Alan L. Porter,et al.  A process for mining science & technology documents databases, illustrated for the case of "knowledge discovery and data mining" , 1999 .

[50]  Z. Griliches.  Patent Statistics as Economic Indicators: a Survey , 1990 .

[51]  Siu Cheung Hui,et al.  Web Mining for Identifying Research Trends , 2003, ICADL.

[52]  Dipankar Dasgupta,et al.  Novelty detection in time series data using ideas from immunology , 1996 .

[53]  Ah-Hwee Tan,et al.  Topic Detection, Tracking, and Trend Analysis Using Self-Organizing Neural Networks , 2001, PAKDD.

[54]  Carlota Perez,et al.  Technological change and opportunities for development as a moving target , 1999 .