Abstract
SOM-based visualization is a promising approach for revealing potential technical solutions varied in patent documents. In this paper, we try to improve the quality of visual representation by constructing Fuzzy Bag-of-Words (FBoW) matrices through utilization of multi-view information. F-term is the special theme code given by the examiners of Japan Patent Office (JPO) for Japanese patent documents and is expected to be a potential candidate of second-view information. Document \(\times \) F-term co-occurrence information is utilized for improving the quality of FBoW representation such that semantical similarities among words are measured by considering F-term semantics. The advantage of utilizing F-term semantics in constructing FBoW is demonstrated through analysis of patent document data.
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Acknowledgment
This work was achieved through the use of large-scale computer systems at the Cybermedia Center, Osaka University, and was supported in part by JSPS KAKENHI Grant Number JP18K11474.
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Nishida, Y., Honda, K. (2020). SOM-Based Visualization of Potential Technical Solutions with Fuzzy Bag-of-Words Utilizing Multi-view Information. In: Huynh, VN., Entani, T., Jeenanunta, C., Inuiguchi, M., Yenradee, P. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2020. Lecture Notes in Computer Science(), vol 12482. Springer, Cham. https://doi.org/10.1007/978-3-030-62509-2_16
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