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Big Data for Prediction: Patent Analysis – Patenting Big Data for Prediction Analysis

Big Data for Prediction: Patent Analysis – Patenting Big Data for Prediction Analysis
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Author(s): Mirjana Pejic-Bach (University of Zagreb, Croatia), Jasmina Pivar (University of Zagreb, Croatia)and Živko Krstić (Atomic Intelligence, Croatia)
Copyright: 2022
Pages: 24
Source title: Research Anthology on Big Data Analytics, Architectures, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-3662-2.ch057

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Abstract

Technical field of big data for prediction lures the attention of different stakeholders. The reasons are related to the potentials of the big data, which allows for learning from past behavior, discovering patterns and values, and optimizing business processes based on new insights from large databases. However, in order to fully utilize the potentials of big data, its stakeholders need to understand the scope and volume of patenting related to big data usage for prediction. Therefore, this chapter aims to perform an analysis of patenting activities related to big data usage for prediction. This is done by (1) exploring the timeline and geographic distribution of patenting activities, (2) exploring the most active assignees of technical content of interest, (3) detecting the type of the protected technical according to the international patent classification system, and (4) performing text-mining analysis to discover the topics emerging most often in patents' abstracts.

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