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Visual patent trend analysis for informed decision making in technology management
Copyright policy )Patent information is increasingly important for decision makers. Their demand for exploratory trend and competitor analysis poses new challenges with respect to the processing and visualization of patent data. We present PatStream: a highly interactive approach for decision support through patent exploration, which offers a streamgraph-based visualization for trends at different levels of abstraction and facilitates the combined analysis of their various aspects, including patent applicants, IPC distributions and innovativeness. PatStream integrates powerful natural language processing techniques for concept extraction and patent similarity assessment to allow for content-oriented visualization and analysis. This work has been partially supported by the European Commission under the grant number FP7-SME-606163 (iPatDoc), and the German Research Foundation (DFG) as part of the priority program 1335 Scalable Visual Analytics.
Microsoft Academic Graph classification: Data science Knowledge management business.industry business Competitor analysis Abstraction (linguistics) Patent visualisation Visualization Computer science Technology management Trend analysis Decision support system Similarity (psychology)
ACM Computing Classification System: ComputingMilieux_LEGALASPECTSOFCOMPUTING
Library and Information Sciences, Computer Science Applications, Process Chemistry and Technology, Energy Engineering and Power Technology, Fuel Technology, Renewable Energy, Sustainability and the Environment, Bioengineering, Patent analysis, Trend analysis, Visualization, Visual analysis, Patent information, Natural language processing
Library and Information Sciences, Computer Science Applications, Process Chemistry and Technology, Energy Engineering and Power Technology, Fuel Technology, Renewable Energy, Sustainability and the Environment, Bioengineering, Patent analysis, Trend analysis, Visualization, Visual analysis, Patent information, Natural language processing
Microsoft Academic Graph classification: Data science Knowledge management business.industry business Competitor analysis Abstraction (linguistics) Patent visualisation Visualization Computer science Technology management Trend analysis Decision support system Similarity (psychology)
ACM Computing Classification System: ComputingMilieux_LEGALASPECTSOFCOMPUTING
- Pompeu Fabra University Spain
- Fraunhofer Society Germany
- University of Wisconsin–Oshkosh United States
- University of Stuttgart Germany
- Pompeu Fabra University Spain
- Fraunhofer Society Germany
- University of Wisconsin–Oshkosh United States
- University of Stuttgart Germany
Patent information is increasingly important for decision makers. Their demand for exploratory trend and competitor analysis poses new challenges with respect to the processing and visualization of patent data. We present PatStream: a highly interactive approach for decision support through patent exploration, which offers a streamgraph-based visualization for trends at different levels of abstraction and facilitates the combined analysis of their various aspects, including patent applicants, IPC distributions and innovativeness. PatStream integrates powerful natural language processing techniques for concept extraction and patent similarity assessment to allow for content-oriented visualization and analysis. This work has been partially supported by the European Commission under the grant number FP7-SME-606163 (iPatDoc), and the German Research Foundation (DFG) as part of the priority program 1335 Scalable Visual Analytics.