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 Patent Text Mining and Semantic Technologies (PatentSemTech 2019). 1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019), Karlsruhe, Germany. https://doi.org/10.34726/pst2019.6
Proceedings of The 1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019)
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Date (published):
2019
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Event name:
1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019)
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Event date:
12-Sep-2019
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Event place:
Karlsruhe, Germany
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Number of Pages:
2
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Keywords:
Patent landscaping; word embeddings; hierarchical clustering; text analysis; semantic exploration; multi-dimensional exploration; visual user interface
en
Additional information:
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.
CC BY 4.0
