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Big Data for Prediction: Patent Analysis – Patenting Big Data for Prediction Analysis (CROSBI ID 62661)

Prilog u knjizi | izvorni znanstveni rad | međunarodna recenzija

Pejić Bach, Mirjana ; Pivar, Jasmina ; Krstić, Živko Big Data for Prediction: Patent Analysis – Patenting Big Data for Prediction Analysis // Big Data Governance and Perspectives in Knowledge Management / Strydom, Moses John ; Kruger Strydom, Sheryl Beverley (ur.). Hershey (PA): IGI Global, 2019. str. 218-240 doi: 10.4018/978-1-5225-7077-6.ch010

Podaci o odgovornosti

Pejić Bach, Mirjana ; Pivar, Jasmina ; Krstić, Živko

engleski

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

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.

big data, patent analysis, prediction

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Podaci o prilogu

218-240.

objavljeno

10.4018/978-1-5225-7077-6.ch010

Podaci o knjizi

Big Data Governance and Perspectives in Knowledge Management

Strydom, Moses John ; Kruger Strydom, Sheryl Beverley

Hershey (PA): IGI Global

2019.

9781522570776

Povezanost rada

Ekonomija, Informacijske i komunikacijske znanosti

Poveznice
Indeksiranost