Abstract
With the promotion of the innovation-driven development strategy, patent data mining is receiving increasing attention, especially patent relation mining. Most current works mine some simple types of patent relations. However, the types of relation in patent are more complex than these simple types. Since realizing technical objectives needs to innovate technical functions in structure, function, application, testing or processing of products, the types of relations are formed by verbs and nouns as well. We propose a model to discover of multi-degree valence relations combined with their context. In the model, The noun/verb association relations are obtained by their contextual similarity. Combined with these association relations, the model discovers diverse patent relation types.
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Zhang, Q., Sun, Y., Liu, W. (2021). Discovering the Diverse Types of Multi-degree Valence Relations Combined with Their Context. In: Abawajy, J., Choo, KK., Xu, Z., Atiquzzaman, M. (eds) 2020 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2020. Advances in Intelligent Systems and Computing, vol 1244. Springer, Cham. https://doi.org/10.1007/978-3-030-53980-1_119
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DOI: https://doi.org/10.1007/978-3-030-53980-1_119
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