Curious to see VantagePoint in action? Download the White Paper, "Coronavirus Disease 2019 (COVID‐19): Bibliographic and text analysis in VantagePoint"  written by our internal analysts challenged with making sense of the explosive growth of SARS-CoV-2 publications in the National Library of Medicine’s NCBI
SARS‐CoV‐2 PubMed dataset. The original research is part of an awarded US National Science Foundation RAPID project, Corona
Virus – Exploring Causes and Cures through Literature Based Discovery.

 See a global view of VantagePoint in action! Visit our VantagePoint dashboard to navigate over 500 published research papers (since 2011) that have used our text-mining software in their analysis. We imported the dataset into VantagePoint itself, grouping by Text-Mining Applications, Text-Mining Methods, Research Topics, and Data Sources. You will see that VantagePoint has been used globally for numerous technology/innovation management applications (competitive technological intelligence, technology roadmapping, policy analysis, etc.) as well as science and innovation policy applications (interdisciplinary research metrics, science maps, research evaluation, etc.).

The UK Intellectual Property office has used VantagePoint to provide technology landscapes on high impact technologies. For a Case Study, see  Graphene - The worldwide patent landscape in 2015.

Alan L. Porter and Scott W. Cunningham

published by Wiley (2005)

Print ISBN:9780471475675 |Online ISBN:9780471698463 |DOI:10.1002/0471698466

Tech Mining makes exploitation of text databases meaningful to those who can gain from derived knowledge about emerging technologies. It begins with the premise that we have the information, the tools to exploit it, and the need for the resulting knowledge.

 The information provided puts new capabilities at the hands of technology managers. Using the material present, these managers can identify and access the most valuable technology information resources (publications, patents, etc.); search, retrieve, and clean the information on topics of interest; and lower the costs and enhance the benefits of competitive technological intelligence operations.

A. Thomas Roper, Scott W. Cunningham, Alan L. Porter, Thomas W. Mason, Frederick A. Rossini, Jerry Banks

published by Wiley (2011)
Print ISBN:9780470440902 |Online ISBN:9781118047989 |DOI:10.1002/9781118047989

See the Table of Contents

Published in 1991, the first edition of Forecasting and Management of Technology was one of the leading handful of books to deal with the topic of forecasting of technology and technology management as this discipline was emerging. The revised edition of this book builds on this knowledge in the context of business organizations that now place a greater emphasis on technology (the Internet; group decision-making including process management and mechanism design; powerful analytical software) to stay on the cutting edge of development. The scope of this edition has broadened to include management of technology content that is relevant now to executives in organizations while updating and strengthening the technology forecasting and analysis content that the first edition is reputed for. Included in this book are 5 case studies from various industries that show how technology management is applied in the real world.

by: Alan L. Porter and Yi Zhang

The Millenium Project provides a well-coordinated set of methods chapters on various aspects of futures research in Futures Research Methodology — Version 3.0  We expanded our chapter on “TECH MINING of Science & Technology Information Resources for Future-oriented Technology Analyses” in March, 2015. The chapter overviews tech mining and spotlights three case analyses:

• The successful case of the Army’s assessment of ceramic coating potential, leading to a new operational program to recondition tank engines
• Canadian Government benchmarking of national photonic research initiatives
• Our incorporation of advanced text analytics to generate Competitive Technical Intelligence (CTI) for Dye-Sensitized Solar Cells (DSSCs) – in particular, to craft a form of Technology RoadMap (TRM)

FRM 3.0 chapter 20-Tech Mining

Samira Ranaei, Arho Suominen, Alan Porter and Tuomo Kässi

The quantitative study of science, technology and innovation (ST&I ) has experienced significant growth with advancements in disciplines such as mathematics, computer science and information sciences. From the early studies utilizing the statistics method, graph theory, to citations or co-authorship, the state of the art in quantitative methods leverages natural language processing and machine learning. However, there is no unified methodological approach within the research community or a comprehensive understanding of how to exploit text-mining potentials to address ST&I research objectives. Therefore, this chapter in Springer Handbook of Science and Technology Indicators (2019) intends to present the state of the art of text mining within the framework of ST&I. The major contribution of the chapter is twofold; first, it provides a review of the literature on how text mining extended the quantitative methods applied in ST&I and highlights major methodological challenges. Second, it discusses two hands-on detailed case studies on how to implement the text analytics routine.

Technological Forecasting and Social Change
Volume 146, September 2019, Pages 628-643

Alan L. Porter, Jon Garner, Stephen F. Carley, and Nils C.Newman
Search Technology, Inc., Norcross, GA, USA

Abstract - Indicators of technological emergence promise valuable intelligence to those determining R&D priorities. We present an implemented algorithm to calculate emergence scores for topical terms from abstract record sets. We offer a family of emergence indicators deriving from those scores. Primary emergence indicators identify “hot topic” terms. We then use those to generate secondary indicators that reflect organizations, countries, or authors especially active at frontiers in a target R&D domain. We also flag abstract records (papers or patents) rich in emergent technology content, and we score research fields on relative degree of emergence. This paper presents illustrative results for example topics – Nano-Enabled Drug Delivery, Non-Linear Programming, Dye Sensitized Solar Cells, and Big Data.

Alan L. Porter and Nils C. Newman, Search Technology, Inc. (CIMS Technology Management Report, pp 17-19, Spring 2011)

"Tech mining is an essential tool for enabling open innovation," wrote Alan L. Porter in the Spring 2011 CIMS Technology Management Report.  He detailed in that article how Tech Mining can help managers in the biotech industry search research publications for answers to "who, what,when,and where?" questions.  Porter and his Search Technology, Inc, colleague Nils C. Newman cull the literature for examples of tech mining successes outside of strictly academic research.  They illustrate the progress being made in applying tech mining more broadly, and also point toward applying these capabilities to the identification of potential technology innovation pathways.  

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