Topic-based technological forecasting based on patent data: A case study of Australian patents from 2000 to 2014

The study of technological forecasting is an important part of patent analysis. Although fitting models can provide a rough tendency of a technical area, the trend of the detailed content within the area remains hidden. It is also difficult to reveal the trend of specific topics using keyword-based text mining techniques, since it is very hard to track the temporal patterns of a single keyword that generally represents a technological concept. To overcome these limitations, this research proposes a topic-based technological forecasting approach, to uncover the trends of specific topics underlying massive patent claims using topic modelling. A topic annual weight matrix and a sequence of topic-based trend coefficients are generated to quantitatively estimate the developing trends of the discovered topics, and evaluate to what degree various topics have contributed to the patenting activities of the whole area. To demonstrate the effectiveness of the approach, we present a case study using 13,910 utility patents that were published during the years 2000 to 2014, owned by Australian assignees, in the United States Patent and Trademark Office (USPTO). The results indicate that the proposed approach is effective for estimating the temporal patterns and forecast the future trends of the latent topics underlying massive claims. The topic-based knowledge and the corresponding trend analysis provided by the approach can be used to facilitate further technological decisions or opportunity discovery.

[1]  Michalis Vazirgiannis,et al.  c ○ 2001 Kluwer Academic Publishers. Manufactured in The Netherlands. On Clustering Validation Techniques , 2022 .

[2]  Silvia Salini,et al.  A decade of research in statistics: a topic model approach , 2015, Scientometrics.

[3]  Thomas L. Griffiths,et al.  Probabilistic Topic Models , 2007 .

[4]  Bart Van Looy,et al.  Inventions shaping technological trajectories: do existing patent indicators provide a comprehensive picture? , 2013, Scientometrics.

[5]  Gregor Heinrich.  Parameter estimation for text analysis , 2009 .

[6]  Duen-Ren Liu,et al.  Discovering competitive intelligence by mining changes in patent trends , 2010, Expert Syst. Appl..

[7]  Reinhilde Veugelers,et al.  Measuring Technological Novelty with Patent-Based Indicators , 2015 .

[8]  Marianela Carrillo,et al.  A new approach to modelling sigmoidal curves , 2002 .

[9]  Elena Novelli,et al.  An examination of the antecedents and implications of patent scope , 2015 .

[10]  K. Idris.  WIPO intellectual property handbook: policy, law and use , 2001 .

[11]  Fred Phillips,et al.  Key ideas from a 25-year collaboration at technological forecasting & social change , 2016 .

[12]  Arho Suominen,et al.  Modeling : Comparison of Unsupervised Learning and Human-Assigned Subject Classification , 2015 .

[13]  Alan L. Porter,et al.  R&D Cluster Quality Measures and Technology Maturity , 2003 .

[14]  Huiping Sun,et al.  CQArank: jointly model topics and expertise in community question answering , 2013, CIKM.

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

[16]  Eamonn J. Keogh,et al.  An online algorithm for segmenting time series , 2001, Proceedings 2001 IEEE International Conference on Data Mining.

[17]  Arho Suominen,et al.  Firms' knowledge profiles: Mapping patent data with unsupervised learning , 2017 .

[18]  Theodore Modis,et al.  Chaoslike states can be expected before and after logistic growth , 1992 .

[19]  Sungjoo Lee,et al.  Modeling and analyzing technology innovation in the energy sector: Patent-based HMM approach , 2012, Comput. Ind. Eng..

[20]  F. Philips,et al.  A method for detecting a shift in a trend , 1999, PICMET '99: Portland International Conference on Management of Engineering and Technology. Proceedings Vol-1: Book of Summaries (IEEE Cat. No.99CH36310).

[21]  Gilbert L. Peterson,et al.  Applicability of Latent Dirichlet Allocation to multi-disk search , 2014, Digit. Investig..

[22]  Jinhyung Kim,et al.  Technology trends analysis and forecasting application based on decision tree and statistical feature analysis , 2012, Expert Syst. Appl..

[23]  Holger Ernst,et al.  The Use of Patent Data for Technological Forecasting: The Diffusion of CNC-Technology in the Machine Tool Industry , 1997 .

[24]  David M. Blei,et al.  Probabilistic topic models , 2012, Commun. ACM.

[25]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[26]  Jie Lu,et al.  A patent time series processing component for technology intelligence by trend identification functionality , 2014, Neural Computing and Applications.

[27]  Alexander von Eye,et al.  Forecasting trends of development of psychology from a bibliometric perspective , 2011, Scientometrics.

[28]  George Athanasopoulos,et al.  Optimally Reconciling Forecasts in a Hierarchy , 2014 .

[29]  Yongtae Park,et al.  How to assess patent infringement risks: a semantic patent claim analysis using dependency relationships , 2013, Technol. Anal. Strateg. Manag..

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

[31]  Subhashini Venugopalan,et al.  Topic based classification and pattern identification in patents , 2015 .

[32]  Murat Bengisu,et al.  Forecasting emerging technologies with the aid of science and technology databases , 2006 .

[33]  Kunio Kashino,et al.  A Quick Search Method for Audio Signals Based on a Piecewise Linear Representation of Feature Trajectories , 2008, IEEE Transactions on Audio, Speech, and Language Processing.

[34]  Joseph Paul Martino,et al.  Technological Forecasting for Decisionmaking , 1975 .

[35]  Von-Wun Soo,et al.  Extract conceptual graphs from plain texts in patent claims , 2012, Eng. Appl. Artif. Intell..

[36]  J. Davidson Frame,et al.  Measuring national technological performance with patent claims data , 1994 .

[37]  Kwangsoo Kim,et al.  TrendPerceptor: A property-function based technology intelligence system for identifying technology trends from patents , 2012, Expert Syst. Appl..

[38]  Min Song,et al.  Time gap analysis by the topic model-based temporal technique , 2014, J. Informetrics.

[39]  George Karypis,et al.  A Comparison of Document Clustering Techniques , 2000 .

[40]  Ying Ding,et al.  Topic-based PageRank on author cocitation networks , 2011, J. Assoc. Inf. Sci. Technol..

[41]  Eamonn J. Keogh,et al.  Segmenting Time Series: A Survey and Novel Approach , 2002 .

[42]  Eamonn J. Keogh,et al.  An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback , 1998, KDD.

[43]  Mark Steyvers,et al.  Finding scientific topics , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[44]  Xi Chen,et al.  Integrating piecewise linear representation and weighted support vector machine for stock trading signal prediction , 2013, Appl. Soft Comput..

[45]  Jeffrey G. Sheldon,et al.  How to Write a Patent Application , 1995 .

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

[47]  Yuen-Hsien Tseng,et al.  Text mining techniques for patent analysis , 2007, Inf. Process. Manag..

[48]  Peg Young,et al.  Technological growth curves. A competition of forecasting models , 1993 .

[49]  John D. Lafferty,et al.  Dynamic topic models , 2006, ICML.

[50]  R. S. Campbell,et al.  Patent trends as a technological forecasting tool , 1983 .

[51]  Sungjoo Lee,et al.  Technology clustering based on evolutionary patterns: The case of information and communications technologies☆ , 2011 .

[52]  Kumiko Miyazaki,et al.  Evaluating the effectiveness of keyword search strategy for patent identification , 2013 .

[53]  Jinho Choi,et al.  Patent keyword network analysis for improving technology development efficiency , 2014 .

[54]  Samee U. Khan,et al.  A literature review on the state-of-the-art in patent analysis , 2014 .

[55]  Alan L. Porter,et al.  Special issue on tech mining , 2006 .

[56]  Pei-Chann Chang,et al.  Integrating a Piecewise Linear Representation Method and a Neural Network Model for Stock Trading Points Prediction , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[57]  Chao-Chan Wu,et al.  Using patent analyses to monitor the technological trends in an emerging field of technology: a case of carbon nanotube field emission display , 2009, Scientometrics.

[58]  Chia-Yon Chen,et al.  Technology forecasting and patent strategy of hydrogen energy and fuel cell technologies , 2011 .

[59]  Oguz K. Baskurt,et al.  Time series analysis of publication counts of a university: what are the implications? , 2011, Scientometrics.