Skripnikova, T., Aras, H., Weißhaar, A., Blank, S., & Zorn, H.-P. (2019). Semantic Views - Interactive Hierarchical Exploration for Patent Landscaping. In Proceedings of the 1st Workshop on on Patent Text Mining and Semantic Technologies / Editors: Linda Andersson, Hidir Aras, Florina Piroi, Allan Hanbury. https://doi.org/10.34726/pst2019.6
E194 - Institut für Information Systems Engineering
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Patent landscaping; word embeddings; hierarchical clustering; text analysis; semantic exploration; multi-dimensional exploration; visual user interface
In this paper, we investigate whether a semantic representation of patent documents provides added value for a multi-dimensional visual exploration of a patent landscape compared to traditional approaches. Word embeddings from a pre-trained model created from patent text are used to calculate pairwise similarities for representing each document in the semantic space. Then, a hierarchical clustering method is applied to create several semantic aggregation levels for a collection of patent documents. For visual exploration, we have seamlessly integrated multiple interaction metaphors that combine semantics and additional metadata for improving hierarchical exploration of large document collections.