| dc.description.abstract | Nowadays, a great number of technologies have been invented and applied in every knowledge area of human beings, especially in the era of Industry 4.0. Technologies are granted and protected by patents. Many software solutions have been developed to exploit patent data for searching and patent map analysis to identify technological trends. However, current solutions have their limitations. Because of the heterogeneity of patent data, many solutions only focus on processing either structured or un-structured aspects of patents. Moreover, the technological trend identification behaviors have problems. Before generating patent maps, user need to construct the query. The queries are inflexible and repeated for construction; users must repeat the process of writing queries, then find information on the patent maps, then re-write the queries with viewed information. Also, many solutions are shortage in search result comparison on patent documents to compare the users’ interests. Furthermore, non-patent expert users have difficulty in identifying technological trends of their interests.
Our contributions are threefold. First, we provide a model for patent data processing on both structured and un-structured data. Second, apart from basic search on patents, we produce methods that boosts the user query construction effectiveness and allow user to compare their interests. Third, we introduce visualization methods on patent map to identify technological trends, by combining structured and unstructured data of patent documents, CPC classification and English thesaurus synonym dictionary which are used to enrich user queries.
Keywords: patent, search, patent map, query construction, comparison, structured data, unstructured data, visualization, CPC, synonym | en_US |
