Tech Mining can be defined as text analyses of ST&I information resources to generate Competitive Technical Intelligence (CTI). It combines bibliometrics and advanced text analytic, drawing on specialized knowledge pertaining to ST&I. Tech Mining may also be viewed as a special form of "Big Data" analytics because it searches on a target emerging technology (or key organization) of interest in global databases. One then downloads, typically, thousands of field-structured text records (usually abstracts), and analyses those for useful CTI. Forecasting Innovation Pathways (FIP) is a methodology drawing on Tech Mining plus additional steps to elicit stakeholder and expert knowledge to link recent ST&I activity to likely future development.

Preface.- Part I: Data Science/Technology Review.- Chapter 1: FTA as Due Diligence for an Era of Accelerated Interdiction by an Algorithm-Big Data Duo.- Chapter 2: A Conceptual Framework of Tech Mining Engineering to Enhance the Planning of Future Innovation Pathways.- Chapter 3: Profile and Trends of FTA and Foresight.- Chapter 4: Recent Trends in Technology Mining Approaches.- Chapter 5: Anticipating Future Pathways of Science, Technology, and Innovations.- Part II: Text Analytic Methods.- Chapter 6: Towards Foresight 3.0--The HCSS Metafore Approach.- Chapter 7: Using Enhanced Patent Data for Future-Oriented Technology Analysis.- Chapter 8: Innovation and Design Process Ontology.- Chapter 9: Generating Competitive Technical Intelligence Using Topical Analysis, Patent Citation Analysis and Term Clumping Analysis.- Chapter 10: Identifying Targets for Technology Mergers and Acquisitions Using Patent Information and Semantic Analysis.- Chapter 11: Identifying Technological Topic Changesin Patent Claims Using Topic Modeling.- Chapter 12: Semi-Automatic Technology Roadmapping Composing Method for Multiple Science, Technology, and Innovation Data Incorporation.- Chapter 13: Generating Futures from Text.- Part III: Anticipating the Future--Cases and Frameworks.- Chapter 14: Additive Manufacturing.- Chapter 15: The Application of Social Network Analysis.- Chapter 16: Building a View of the Future of Antibiotics Through the Analysis of Primary Patents.- Chapter 17: Combining Scientometics with Patent-Metrics for CTI Service in R&D Decision Making.- Chapter 18: Tech Mining for Emerging STI Trends through Dynamic Term Clustering and Semantic Analysis: The Case of Photonics.