IEEE Transactions on
Special Issue: Tech Mining
This issue is being developed through
Alan Porter firstname.lastname@example.org
Yi Zhang Yi.Zhang@uts.edu.au
Denise Chiavetta email@example.com
Tech Mining, a special form of “Big Data” analytics, aims to generate practical intelligence using bibliometric and text-mining software as well as other analytical & visualization applications for analyses of Science, Technology & Innovation (ST&I) information resources. Management and policy target uses include Competitive Technical Intelligence (CTI), and university, government, and industry research management (enriching grant applications, scoping projects, avoiding redundant research, and assessing R&D effectiveness). The goal of the special issue is to advance the use of textual information in multiple science, technology, and business development fields by addressing the following key challenges:
- Maximizing potential of traditional and novel text data: Tapping vital traits while minding limitations and matching analytical aims. Data topics of interest include:
- resolving data hygiene issues generated by multiple sources
- ways to address newer data sources (e.g., web scraping, social media cumulations)
- transitioning from database mining to real-time streaming text-analytics
- data structures and lattices
- Advancing and integrating methods. Topics of interest include:
- tracking emergence by extracting topical content via advanced natural language processing, term clumping, topic modelling, etc.
- ways to demonstrate multi-dimensional indicators of R&D & innovation activity
- means to combine quantitative and qualitative approaches in practical case applications
- algorithms for identification of emergence (of technologies and inception of notable innovations)
- discovering the higher-level properties of (complex) social networks
- Translating analyses to useful intelligence: Informative indicators and compelling visualizations.
- case studies that offer testable projections (specific, explicit) to enable future revisiting to validate methods.
- visual analytics capabilities, both for analysts and for end-users
While this issue is being developed in collaboration with the Global TechMining Conference (GTM) 2018 to be held in Leiden, 11 September 2018, papers outside the conference are welcome.
Submission Process: Please prepare the manuscript according to IEEE-TEM’s guidelines (http://ieee-tmc.org/tem-guidelines) and submit tt the journal’s Manuscript Central site (https://mc.manuscriptcentral.com/tem-ieee). Please clearly state in the cover letter that the submission is for this special issue.
Interested authors send abstracts by November 30th 2018
Decisions on acceptance of abstracts by February 28th 2019
Papers submitted by August 31st 2019
IEEE Transactions on Engineering Management is journal of the Technology and Engineering Management Society of IEEE, published quarterly since 1954. It is dedicated to the publication of peer-reviewed original contributions, by researchers and practitioners, regarding the theory and practice of engineering, technology, and innovation management.
Editor in Chief
Tugrul U Daim, PhD PICMET Fellow
Professor and Director
Technology Management Doctoral Program
Department of Engineering and Technology Management
Maseeh College of Engineering and Computer Science
Portland State University, Portland OR