NDLI: Unsupervised learning based patent landscapes using full-text patent data

Content Provider	IEEE Xplore Digital Library
Author	Suominen, A. Toivanen, H.
Copyright Year	2014
Description	Author affiliation: VTT (Tech. Res. Centre of Finland), Espoo, Finland (Suominen, A.; Toivanen, H.)
Abstract	The complexity technologies require that companies have in-depth knowledge of the nature and effect of knowledge - its depth and breadth. Companies need to master expanding technological knowledge bases creating tensions for MOT. We examine how big data in patent landscaping creates insights into MOT. Using big data to manage Competitive Technical Intelligence, companies can foster new forms of adaptive learning processes in MOT. This however requires that managers augment human judgment with machine-learning tools, prompting challenges to management traditions. We demonstrate how unsupervised learning creates insight into MOT by identifying topical knowledge foci and showing the dynamics of knowledge domains among companies. Using unsupervised learning and network analysis; we show how a semantic analysis leads to the identification of opportunities in complex environments. We illustrate this using a case in globally operating telecommunication companies using a full-text copy of USPTO-database with approximately 6 million patents data. Our results show the landscape of the companies and the underlying knowledge embedded in the companies. We discuss how managers can evaluate their technological knowledge against competitors, balancing current needs with the adoption of new knowledge. We further discuss how a semantic analysis can lead to the discovery of latent patterns and identification of opportunities.
Sponsorship	Panasonic Syst. Commun. Co. of N. Am. Travel Portland
Starting Page	2195
Ending Page	2203
File Size	568784
Page Count	9
File Format	PDF
e-ISBN	9781890843311
DOI	10.1109/PICMET.2015.7273139
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-02
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Portland International Conference on Management of Engineering and Technology
Subject Keyword	Patents Companies Unsupervised learning Big data Industries Semantics Data mining
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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