[1] M. Abadi et al.: “TensorFlow: Large-scale machine learning on heterogeneous systems.” [Online]. Available: https://www.tensorflow.org/
[2] M. R. Anderberg (著), 西田英郎 (監訳): クラスター分析とその応用, 内田老鶴圃, 1988.
[3] J. C. Bezdek and R. J. Hathaway: “VAT: A tool for visual assessment of (cluster) tendency,” Proc. 2002 Int’l Joint Conf. Neural Networks, pp. 2225-2230, 2002.
[4] J. C. Bezdek, R. J. Hathaway, and J. M. Huband: “Visual assessment of clustering tendency for rectangular dissimilarity matrices,” IEEE Transactions on Fuzzy Systems, Vol. 15, No. 5, pp. 890- 903, 2007.
[5] S. Bickel and T. Scheffer: “Multi-view clustering,” Proc. of the 4th IEEE International Conference on Data Mining, pp. 19-26, 2004.
[6] C. M. Bishop, M .Svens´en, and C. K. I. Williams: “GTM: The generative topographic mapping,” Neural Computation, Vol. 10, No. 1, pp. 215-234, 1998.
[7] P. Bojanowski, E. Grave, A. Joulin, and T. Mikolov: “Enriching word vectors with subword infor- mation,” Transactions of the Association for Computational Linguistics, Vol. 5, pp. 135-146, 2017.
[8] J. Devlin, M.-W. Chang, K. Lee, T. Kenton, and K. Toutanova: “BERT: Pre-training of deep bidirectional transformers for language understanding,” Proc. of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Vol. 1, pp. 4171-4186, 2018.
[9] C. Ding and X. He: “Linearized cluster assignment via spectral ordering,” Proc. of Int’l Conf. Machine Learning, pp. 233-240, 2004.
[10] P. F. Drucker (著), 林宏子 (訳): DIAMOND ハーバード・ビジネス・レビュー(2018 年 9 月号), ダイヤモンド社, 2018.
[11] 藤嶋昭, 渡部俊也, 橋本和仁: 光触媒のしくみ, 日本実業出版社, 2000.
[12] H. Furlong: “Trending: Beverage Makers Turning Production Waste Into Biomass, Carbona- tion,” 2016. [Online]. Available: https://sustainablebrands.com/read/cleantech/trending-beverage- makers-turning-production-waste-into-biomass-carbonation
[13] K. Honda, T. Yamamoto, A. Notsu, and H. Ichihashi: “Visualization of non-euclidean relational data by robust linear fuzzy clustering based on FCMdd framework,” Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.17, No.2, pp.312-317, 2013.
[14] K. Honda, N. Yamamoto, S. Ubukata, and A. Notsu: “Noise rejection in MMMs-induced fuzzy co-clustering,” Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 21, No. 7, pp. 1144-1151, 2017.
[15] K. Honda, T. Sako, S. Ubukata, and A. Notsu: “Visual co-cluster assessment with intuitive cluster validation through cooccurrence-sensitive ordering,” Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 22, No. 5, pp. 585-592, 2018.
[16] S. Joglekar: “Self-Organizing Maps with Google’s TensorFlow,” 2015. [Online]. Available: https://codesachin.wordpress.com/2015/11/28/self-organizing-maps-with-googles-tensorflow/
[17] T. Kohonen: Self-Organizing Maps, 3rd ed., Springer, 2000.
[18] 國府久嗣, 山崎治子, 野坂政司: “内容推測に適したキーワード抽出のための日本語ストップワード,” 日本感性工学会論文誌, Vol.12, No.4, pp.511-518, 2013.
[19] 高エネルギー加速器研究機構プレスリリース: “塩が界面活性剤のように振る舞う現象を発見-液体に現れる新しい構造-,” NewsKEK 09-13, 2009.
[20] K. Kummamuru, A. Dhawale, and R. Krishnapuram: “Fuzzy co-clustering of documents and key- words,” Proc. 2003 IEEE Int’l Conf. Fuzzy Systems, Vol. 2, pp. 772-777, 2003.
[21] J. Lampinen and E. Oja: “Clustering properties of hierarchical self-organizing maps,” Journal of Mathematical Imaging and Vision, Vol. 2, pp. 261-272, 1992.
[22] M. Lan, C. L. Tan, J. Su, and Y. Lu: “Supervised and traditional term weighting methods for automatic text categorization,” IEEE Trans. Pattern Anal. Mach. Intell., Vol. 31, No. 4, pp. 721- 735, 2009.
[23] J. B. MacQueen: “Some methods of classification and analysis of multivariate observations,” Proc. of 5th Berkeley Symposium on Math. Stat. and Prob., pp. 281-297, 1967.
[24] 増子由起, 齊藤史哲, 石津昌平: “感情極性値に基づいた印象に曖昧さを含むオノマトペの可視化 -自己組織化マップによる文書データの分析-,” 日本知能情報ファジィ学会誌, Vol. 28, No. 3, pp. 685-691, 2016.
[25] D. Michler, N. Shahidzadeh, M. Westbroek, R. van Roij, and D. Bonn: “Are antagonistic salts surfactants?,” Langmuir, Vol. 31, No. 3, pp. 906-911, 2015.
[26] T. Mikolov, K. Chen, G. S. Corrado, and J. Dean: “Efficient estimation of word representations in vector space,” arXiv preprint, arXiv:1301.3781, 2013.
[27] T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean: “Distributed representations of words and phrases and their compositionality,” Proc. of the 26th International Conference on Neural Information Processing Systems, Vol. 2, pp. 3111-3119, 2013.
[28] 中尾索也, 本多克宏, 野津 亮: “Alternative c-Means 基準を用いたロバストな局所的主成分分析による多次元データの 2 次元視覚化,” 日本知能情報ファジィ学会誌,Vol.26,No.3,pp.718-727,2014.
[29] 西田泰士, 本多克宏: “SOM を用いた特許文献データ分析によるイノベーション加速の可能性について,” 第 33 回ファジィシステムシンポジウム講演論文集, pp. 513-514, 2017.
[30] 西田泰士, 本多克宏: “イノベーション加速のための自己組織化マップによる解決手段の可視化,” 日本知能情報ファジィ学会誌, Vol. 30, No. 2, pp. 543-547, 2018.
[31] Y. Nishida and K. Honda: “Visualization of potential technical solutions by self-organizing maps and co-cluster extraction,” Proc. of Joint 10th International Conference on Soft Computing and In- telligent Systems and 19th International Symposium on Advanced Intelligent Systems in conjunction with Intelligent Systems Workshop 2018, pp. 820-825, 2018.
[32] Y. Nishida and K. Honda: “A comparative study on SOM-based visualization of potential technical solutions using fuzzy bag-of-words and co-occurrence probability of technical words,” Proc. of 7th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, Lecture Notes in Artificial Intelligence 11471, pp. 360-369, 2019.
[33] Y. Nishida and K. Honda: “Visualization of potential technical solutions by SOM and co-clustering and its extension to multi-view situation,” Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 24, No. 1, pp. 65-72, 2020.
[34] Y. Nishida and K. Honda: “SOM-based visualization of potential technical solutions with fuzzy bag-of-words utilizing multi-view information,” Proc. of 8th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, Lecture Notes in Artificial Intelligence 12482, pp. 187-198, 2020.
[35] 小川和晃, 田村哲嗣, 速水悟: “商品レビューにおける時系列情報に着目したクラスタ分析と可視化,” 人工知能学会全国大会論文集, #1F5-5, 2016.
[36] C.-H. Oh, K. Honda, and H. Ichihashi: “Fuzzy clustering for categorical multivariate data,” Proc. of Joint 9th IFSA World Congress and 20th NAFIPS International Conference, pp. 2154-2159, 2001.
[37] A. F. Osborn, Your Creative Power, Scribner, 1948.
[38] A. F. Osborn, Applied imagination, Scribner, 1953.
[39] 大島裕明, 中村聡史, 田中克己: “SlothLib: Web サーチ研究のためのプログラミングライブラリ,” 日本データベース学会 Letters, Vol. 6, No. 1, pp. 113-116, 2007.
[40] M. E. Peters, M. Neumann, M. Iyyer, M. Gardner, C. Clark, K. Lee, and L. Zettlemoyer: “Deep con- textualized word representations,” Proc. of the 2018 the Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp. 2227-2237, 2018.
[41] V. F. Pivovarov, M. S. Gins, and V. K. Gins: “Innovative beverage production technologies based on Amaranth biomass,” Proc. of International Conference on Sustainable Development of Cross-Border Regions, IOP Conf. Series: Earth and Environmental Science 395, #012090, 2019.
[42] T. Ramesh, B. Nayak, A. Amirbahman, C. P. Tripp, and S. Mukhopadhyay: “Application of ul- traviolet light assisted titanium dioxide photocatalysis for food safety: A review,” Innovative Food Science & Emerging Technologies, Vol. 38, Part A, pp. 105-115, 2016.
[43] R. Rˇeh˚uˇrek and P. Sojka: “Software framework for topic modelling with large corpora,” Proc. of the LREC 2010 Workshop on New Challenges for NLP Frameworks, pp. 45-50, 2010.
[44] 齊藤史哲: “Web カスタマーレビュー文の理解支援を目的とした自己組織化マップによる評価分布の可視化法,” 日本経営工学会論文誌, Vol. 65, No.3, pp. 180-190, 2014.
[45] 佐古拓也, 本多克宏, 生方誠希, 野津亮: “Spectral Ordering に基づく共クラスタ構造の視覚化とその特徴,” システム制御情報学会論文誌, Vol. 31, No. 5, pp. 177-183, 2018.
[46] G. Salton and C. Buckley: “Term-weighting approaches in automatic text retrieval,” Information Processing and Management, Vol. 24, No. 5, pp. 513-523, 1988.
[47] 佐藤敏紀, 橋本泰一, 奥村学: “単語分かち書き辞書 mecab-ipadic-NEologd の実装と情報検索における効果的な使用方法の検討,” 言語処理学会年次大会発表論文集, #B6-1, 2017.
[48] T. Sato: “Neologism dictionary based on the language resources on the web for mecab,” 2015. [Online]. Available: https://github.com/neologd/mecab-ipadic-neologd
[49] I. Schellner: “Japanese file index classification and F-terms,” World Patent Information, Vol. 24, pp. 197-201, 2002.
[50] 高橋仁, 中川博之, 土屋達弘: “文書中の単語出現頻度を利用したトピックモデル洗練化,” 情報処理学会研究報告ソフトウェア工学(SE), Vol. 2017-SE-195, No. 22, pp. 1-8, 2017.
[51] 徳高平蔵, 藤村喜久郎, 大北正昭: “球面 SOM を用いたクラスタ分析,” バイオメディカル・ファジィ・システム学会誌, Vol. 8, No. 1, pp. 29-39, 2006.
[52] 角田朗: “特許分類について,” 情報の科学と技術, Vol. 66, No. 2, pp. 266-271, 2016.
[53] L. J. P. van der Maaten and G. E. Hinton: “Visualizing data using t-SNE,” Journal of Machine Learning Research, Vol. 9, pp. 2431-2456, 2008.
[54] Y. M. Xu, C. D. Wang, and J. H. Lai: “Weighted multi-view clustering with feature reduction,” Pattern Recognition, Vol. 53, pp. 25-35, 2016.
[55] 谷中瞳, 大澤幸生: “特許文献を利用した技術課題の抽象化方法の検討,” 人工知能学会全国大会論文集, #1J3-2, 2016.
[56] H. Yanaka and Y. Ohsawa: “Clustering documents on case vectors represented by predicate-argument structures - applied for eliciting technological problems from patents,” Proc. of 2016 Federated Con- ference on Computer Science and Information Systems, Vol. ACSIS-8, pp. 175-180, 2016.
[57] Y. Yang and H. Wang: “Multi-view clustering: A survey,” Big Data Mining and Analytics, Vol. 1, pp. 83-107, 2018.
[58] J. W. Young (著), 今井茂雄 (訳): アイデアのつくり方, CCC メディアハウス, 1988.
[59] L. Zhao and K. Mao: “Fuzzy bag-of-words model for document representation,” IEEE Trans. Fuzzy Systems, Vol. 26, No. 2, pp. 794-804, 2018.