Abstract
Self-Organizing Maps (SOM) is a powerful tool in visualizing mutual connection among various objects. In a previous work, SOM-based visualization was applied for revealing potential technical solutions varied in Japanese patent documents, in which meaningful pairs of technical words are implied in SOMs. Before application, text documents were quantified into numerical vectors considering co-occurrence frequency among technical words in sentences, and then, SOMs were constructed summarizing word features of co-occurrence probability vectors or correlation coefficient vectors. Recently, a fuzzy bag-of-words model was proposed for handling sparse characteristics of word feature values and shown to be useful in document classification. In this paper, a comparative study on utilizing fuzzy bag-of-words in conjunction with previous feature values is performed with the goal of revealing potential technical solutions varied in patent documents.
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Acknowledgment
This work was achieved through the use of large-scale computer systems at the Cybermedia Center, Osaka University.
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Nishida, Y., Honda, K. (2019). A Comparative Study on SOM-Based Visualization of Potential Technical Solutions Using Fuzzy Bag-of-Words and Co-occurrence Probability of Technical Words. In: Seki, H., Nguyen, C., Huynh, VN., Inuiguchi, M. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2019. Lecture Notes in Computer Science(), vol 11471. Springer, Cham. https://doi.org/10.1007/978-3-030-14815-7_30
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DOI: https://doi.org/10.1007/978-3-030-14815-7_30
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