WordNet: a lexical database for English
Communications of the ACM
A vector space model for automatic indexing
Communications of the ACM
Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data
Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data
Introduction to the special issue on patent processing
Information Processing and Management: an International Journal
A novel method for measuring semantic similarity for XML schema matching
Expert Systems with Applications: An International Journal
A simple and fast algorithm for K-medoids clustering
Expert Systems with Applications: An International Journal
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Patent maps showing competition trends in technological development can provide valuable input for decision support on research and development (R&D) strategies. By introducing semantic patent analysis with advantages in representing technological objectives and structures, this paper constructs dynamic patent maps to show technological competition trends and describes the strategic functions of the dynamic maps. The proposed maps are based on subject-action-object (SAO) structures that are syntactically ordered sentences extracted using the natural language processing of the patent text; the structures of a patent encode the key findings of the invention and expertise of its inventors. Therefore, this paper introduces a method of constructing dynamic patent maps using SAO-based content analysis of patents and presents several types of dynamic patent maps by combining patent bibliographic information and patent mapping and clustering techniques. Building on the maps, this paper provides further analyses to identify technological areas in which patents have not been granted ("patent vacuums"), areas in which many patents have actively appeared ("technological hot spots"), R&D overlap of technological competitors, and characteristics of patent clusters. The proposed analyses of dynamic patent maps are illustrated using patents related to the synthesis of carbon nanotubes. We expect that the proposed method will aid experts in understanding technological competition trends in the process of formulating R&D strategies.