Notice of Violation of IEEE Publication Principles: Discovery of Technology Trends from Patent Data on the Basis of Predictive Analytics

Notice of Violation of IEEE Publication Principles

"Discovery of technology trends from patent data on the basis of predictive analytics"
by D. Prokhorenkov and P. Panfilov
in the Proceedings of the IEEE 20th Conference on Business Informatics, 2018, pp.148-152

After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

This paper has copied content from the papers cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.

"Identifying promising technologies using patents: A retrospective feature analysis and a prospective needs analysis on outlier patents"
by Kisik Song, Kyuwoong Kim, and Sungjoo Lee
in Technological Forecasting and Social Change, November 2017

"A Literature Review on the state-of-the-art on Intellectual Property Analytics"
by Leonidas Aristodemou and Frank Tietze
in the University of Cambridge Repository, January 2018

"Exploring the Future of Patent Analytics: A Technology Roadmapping approach"
by Leonidas Aristodemou, Frank Tietze, Nikoletta Athanassopoulou, and Tim Minshall
in Centre for Technology Management working paper series, November 2017

"Exploring the Future of Patent Analytics"
by Leonidas Aristodemou and Frank Tietze
in the University of Cambridge Repository, 2017


Companies are increasingly paying close attention to the IP portfolio, which is a key competitive advantage, so patents and patent applications, as well as analysis and identification of future trends, become one of the important and strategic components of a business strategy. We argue that the problems of identifying and predicting trends or entities, as well as the search for technical features, can be solved with the help of easily accessible Big Data technologies, machine learning and predictive analytics, thereby offering an effective plan for development and progress. The purpose of this study is twofold, the first is an identification of technological trends, the second is an identification of application areas and/or that are most promising in terms of technology development and investment. The research was based on methods of clustering, processing of large text files and search queries in patent databases. The suggested approach is considered on the basis of experimental data in the field of moving connected UAVs and passive acoustic ecology control.