Beyond 5G (B5G)是最新的行動網路通訊技術，可以為未來許多產業實現創新發展與應用。對於現有的B5G專利進行分析可以了解現有市場布局，因此本研究主要利用專利來探索B5G的領域知識和商業化技術趨勢，發展基於機器學習的數據分析方法，並以敘述統計輔助分析。對於領域專利進行文字探勘之主題分析與關鍵字萃取，以探索B5G主要技術。並透過圖卷積網路 (Graph Convolutional Network, GCN)來聚合專利特徵與引用關係以生成專利向量，再運用分群演算法為專利向量分群。藉由每一群的關鍵字、主題分布、引用關係與專利數量變化探索主要技術跟分析科技發趨勢，並加強B5G 知識本體結構。本研究的方法可以對領域專利提取核心的商業化技術與快速了解技術間的關係，並協助生成完整的知識本體以進行知識管理。

Beyond 5G (B5G) is the latest mobile communication technology that can realize innovative development and applications for many industries in the future. Analysis of existing B5G patents can help understand the development of existing technologies. Therefore, this study mainly uses patents to explore B5G domain knowledge and commercialization technology trends, develop machine learning-based data analysis methods, and use narrative statistics to assist. Topic model and keyword extraction of text mining for domain patents to explore the main technologies of B5G. Graph Convolutional Network (GCN) is used to aggregate patent features and citation structures to generate patent vectors. Then, k-means clustering algorithm clusters patent vectors. The main technologies and technological development trends are explored through the keywords, topic distributions and citation relationships of each cluster, and strengthen the B5G ontology. After analyzing the domain patents using the method of this study, we can extract the core commercial technologies, quickly understand the relationship between technologies, and assist in generating a complete knowledge ontology for knowledge management.

1. Akhtar, M. W., Hassan, S. A., Ghaffar, R., Jung, H., Garg, S., & Hossain, M. S. (2020). The shift to 6G communications: vision and requirements. Human-centric Computing and Information Sciences, 10(1). doi:10.1186/s13673-020-00258-2
2. Al-Shibly, M. A. M., Habaebi, M. H., & Chebil, J. (2012). Carrier aggregation in long term evolution-advanced. Paper presented at the 2012 IEEE Control and System Graduate Research Colloquium.
3. Alghamdi, R., & Alfalqi, K. (2015). A survey of topic modeling in text mining. Int. J. Adv. Comput. Sci. Appl.(IJACSA), 6(1).
4. Alghamdi, R., Alhadrami, R., Alhothali, D., Almorad, H., Faisal, A., Helal, S., . . . Alouini, M.-S. (2020). Intelligent Surfaces for 6G Wireless Networks: A Survey of Optimization and Performance Analysis Techniques. IEEE Access, 8, 202795-202818. doi:10.1109/access.2020.3031959
5. Ali, M. S. (2014). On the evolution of coordinated multi-point (CoMP) transmission in LTE-advanced. International Journal of Future Generation Communication and Networking, 7(4), 91-102.
6. Ali, S., Saad, W., Steinbach, D., Ahmad, I., & Huusko, J. (2020). White Paper on Machine Learning in Wireless Communication Networks.
7. An, J., Kim, K., Mortara, L., & Lee, S. (2018). Deriving technology intelligence from patents: Preposition-based semantic analysis. Journal of Informetrics, 12(1), 217-236.
8. Arya, K. V., Bhadoria, R. S., & Chaudhari, N. S. (2018). Emerging Wireless Communication and Network Technologies: Principle, Paradigm and Performance: Springer.
9. Ault, S. V., Perez, R. J., Kimble, C. A., & Wang, J. (2018). On speech recognition algorithms. International Journal of Machine Learning and Computing, 8(6), 518-523.
10. Bansal, S., & Kumar, D. (2020). IoT ecosystem: A survey on devices, gateways, operating systems, middleware and communication. International Journal of Wireless Information Networks, 27(3), 340-364.
11. Beaubrun, R., Moulin, B., & Jabeur, N. (2007). An architecture for delivering location-based services. International Journal of Computer Science and Network Security, 7(7), 160-166.
12. Bezdek, J. C., Ehrlich, R., & Full, W. (1984). FCM: The fuzzy c-means clustering algorithm. Computers & geosciences, 10(2-3), 191-203.
13. Borst, P., Akkermans, H., & Top, J. (1997). Engineering ontologies. International journal of human-computer studies, 46(2-3), 365-406.
14. Braam, R. R., Moed, H. F., & Van Raan, A. F. (1991a). Mapping of science by combined co‐citation and word analysis. I. Structural aspects. Journal of the American Society for information science, 42(4), 233-251.
15. Braam, R. R., Moed, H. F., & Van Raan, A. F. (1991b). Mapping of science by combined co‐citation and word analysis. II: Dynamical aspects. Journal of the American Society for information science, 42(4), 252-266.
16. Callon, M., Courtial, J.-P., Turner, W. A., & Bauin, S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social science information, 22(2), 191-235.
17. Campos, R., Mangaravite, V., Pasquali, A., Jorge, A., Nunes, C., & Jatowt, A. (2020). YAKE! Keyword extraction from single documents using multiple local features. Information Sciences, 509, 257-289. doi:10.1016/j.ins.2019.09.013
18. Chakraborty, M., Byshkin, M., & Crestani, F. (2020). Patent citation network analysis: A perspective from descriptive statistics and ERGMs. Plos one, 15(12), e0241797.
19. Chandrasekaran, B., Josephson, J. R., & Benjamins, V. R. (1999). What are ontologies, and why do we need them? IEEE Intelligent Systems and their applications, 14(1), 20-26.
20. Chang, P.-L., Wu, C.-C., & Leu, H.-J. (2010). Using patent analyses to monitor the technological trends in an emerging field of technology: a case of carbon nanotube field emission display. Scientometrics, 82(1), 5-19.
21. Chen, P., & Liu, S. (2010). Intelligent vehicle monitoring system based on GPS, GSM and GIS. Paper presented at the 2010 WASE International Conference on Information Engineering.
22. Chien, W.-C., Cho, H.-H., Lai, C.-F., Tseng, F.-H., Chao, H.-C., Hassan, M. M., & Alelaiwi, A. (2019). Intelligent architecture for mobile HetNet in B5G. IEEE Network, 33(3), 34-41.
23. Cobo, M. J., López‐Herrera, A. G., Herrera‐Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for information Science and Technology, 62(7), 1382-1402.
24. Cummings, D., & Nassar, M. (2020). Structured citation trend prediction using graph neural networks. Paper presented at the ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
25. Deakin, M., & Mora, L. (2019). Untangling Smart Cities: From Theory to Practice: Elsevier.
26. Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805.
27. Dornis, T. W. (2020). Standard-Essential Patents and FRAND Licensing—At the Crossroads of Economic Theory and Legal Practice. Journal of European Competition Law & Practice, 11(10), 575-591.
28. Ebesu, T., & Fang, Y. (2017). Neural citation network for context-aware citation recommendation. Paper presented at the Proceedings of the 40th international ACM SIGIR conference on research and development in information retrieval.
29. Elgala, H., Mesleh, R., & Haas, H. (2011). Indoor optical wireless communication: potential and state-of-the-art. IEEE Communications Magazine, 49(9), 56-62.
30. Ercan, G., & Cicekli, I. (2007). Using lexical chains for keyword extraction. Information Processing & Management, 43(6), 1705-1714.
31. Ester, M., Kriegel, H.-P., Sander, J., & Xu, X. (1996). A density-based algorithm for discovering clusters in large spatial databases with noise. Paper presented at the kdd.
32. European Telecommunications Standards Institute. (2022). DYNAMIC REPORTING. Retrieved from https://ipr.etsi.org/DynamicReporting.aspx
33. Fey, M., & Lenssen, J. E. (2019). Fast graph representation learning with PyTorch Geometric. arXiv preprint arXiv:1903.02428.
34. Fout, A. M. (2017). Protein interface prediction using graph convolutional networks. Colorado State University,
35. Gallagher, R. J., Reing, K., Kale, D., & Ver Steeg, G. (2017). Anchored correlation explanation: Topic modeling with minimal domain knowledge. Transactions of the Association for Computational Linguistics, 5, 529-542.
36. Gandotra, P., Jha, R. K., & Jain, S. (2017). A survey on device-to-device (D2D) communication: Architecture and security issues. Journal of Network and Computer Applications, 78, 9-29.
37. Garcia, M. H. C., Molina-Galan, A., Boban, M., Gozalvez, J., Coll-Perales, B., Şahin, T., & Kousaridas, A. (2021). A tutorial on 5G NR V2X communications. arXiv preprint arXiv:2102.04538.
38. Glänzel, W. (2001). National characteristics in international scientific co-authorship relations. Scientometrics, 51(1), 69-115.
39. Govindarajan, U. H., Trappey, A. J., & Trappey, C. V. (2019). Intelligent collaborative patent mining using excessive topic generation. Advanced Engineering Informatics, 42, 100955.
40. Grootendorst, M. (2020). Bertopic: Leveraging bert and c-tf-idf to create easily interpretable topics. Version v0, 4.
41. Grover, A., & Leskovec, J. (2016). node2vec: Scalable feature learning for networks. Paper presented at the Proceedings of the 22nd ACM SIGKDD international conference on Knowledge discovery and data mining.
42. Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge acquisition, 5(2), 199-220.
43. Guarino, N., Oberle, D., & Staab, S. (2009). What is an ontology? In Handbook on ontologies (pp. 1-17): Springer.
44. Habibi, M. A., Nasimi, M., Han, B., & Schotten, H. D. (2019). A comprehensive survey of RAN architectures toward 5G mobile communication system. IEEE Access, 7, 70371-70421.
45. Hamaguchi, T., Oiwa, H., Shimbo, M., & Matsumoto, Y. (2017). Knowledge transfer for out-of-knowledge-base entities: A graph neural network approach. arXiv preprint arXiv:1706.05674.
46. Hamilton, W. L. (2020). Graph representation learning. Synthesis Lectures on Artifical Intelligence and Machine Learning, 14(3), 1-159.
47. Huang, J., Wang, C.-X., Chang, H., Sun, J., & Gao, X. (2020). Multi-Frequency Multi-Scenario Millimeter Wave MIMO Channel Measurements and Modeling for B5G Wireless Communication Systems. IEEE Journal on Selected Areas in Communications, 38(9), 2010-2025. doi:10.1109/jsac.2020.3000839
48. Jain, A. K. (2010). Data clustering: 50 years beyond K-means. Pattern recognition letters, 31(8), 651-666.
49. Jain, A. K., Murty, M. N., & Flynn, P. J. (1999). Data clustering: a review. ACM computing surveys (CSUR), 31(3), 264-323.
50. Ji, H., Park, S., Yeo, J., Kim, Y., Lee, J., & Shim, B. (2018). Ultra-reliable and low-latency communications in 5G downlink: Physical layer aspects. IEEE Wireless Communications, 25(3), 124-130.
51. Johnson, S. C. (1967). Hierarchical clustering schemes. Psychometrika, 32(3), 241-254.
52. Jones, K. S. (1973). Index term weighting. Information storage and retrieval, 9(11), 619-633.
53. Joung, J., & Kim, K. (2017). Monitoring emerging technologies for technology planning using technical keyword based analysis from patent data. Technological Forecasting and Social Change, 114, 281-292.
54. Jungnickel, V., Thiele, L., Wirth, T., Haustein, T., Schiffermuller, S., Forck, A., . . . Gabler, H. (2009). Coordinated multipoint trials in the downlink. Paper presented at the 2009 IEEE Globecom Workshops.
55. Junior, R. R. R., Vieira, M. A., & Loureiro, A. A. (2018). Dynamic link aggregation in software defined networking. Paper presented at the 2018 IEEE Symposium on Computers and Communications (ISCC).
56. Krestel, R., Chikkamath, R., Hewel, C., & Risch, J. (2021). A survey on deep learning for patent analysis. World Patent Information, 65, 102035.
57. Kuvaja, A., & Mäkinen, O. (2006). UNLICENSED MOBILE ACCESS. Innovation in Telecommunications, 74.
58. Lam, D., & Wunsch, D. C. (2014). Clustering. Academic Press Library in Signal Processing, 1, 1115-1149.
59. Larsson, E. G., Edfors, O., Tufvesson, F., & Marzetta, T. L. (2014). Massive MIMO for next generation wireless systems. IEEE Communications Magazine, 52(2), 186-195.
60. Latva-aho, M., Leppänen, K., Clazzer, F., & Munari, A. (2020). Key drivers and research challenges for 6G ubiquitous wireless intelligence.
61. Lee, J.-S., & Hsiang, J. (2020). Patent classification by fine-tuning BERT language model. World Patent Information, 61, 101965.
62. Li, D., Li, S., Li, W., Wang, W., & Qu, W. (2010). A semi-supervised key phrase extraction approach: learning from title phrases through a document semantic network. Paper presented at the Proceedings of the ACL 2010 conference short papers.
63. Liang, H., Sun, X., Sun, Y., & Gao, Y. (2017). Text feature extraction based on deep learning: a review. EURASIP journal on wireless communications and networking, 2017(1), 1-12.
64. Liu, H., Darabi, H., Banerjee, P., & Liu, J. (2007). Survey of wireless indoor positioning techniques and systems. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 37(6), 1067-1080.
65. Liu, Y., & Lapata, M. (2019). Text summarization with pretrained encoders. arXiv preprint arXiv:1908.08345.
66. Liu, Z., Li, P., Zheng, Y., & Sun, M. (2009). Clustering to find exemplar terms for keyphrase extraction. Paper presented at the Proceedings of the 2009 conference on empirical methods in natural language processing.
67. Lopez-Perez, D., Guvenc, I., De la Roche, G., Kountouris, M., Quek, T. Q., & Zhang, J. (2011). Enhanced intercell interference coordination challenges in heterogeneous networks. IEEE Wireless Communications, 18(3), 22-30.
68. Love, D. J., Heath, R. W., Santipach, W., & Honig, M. L. (2004). What is the value of limited feedback for MIMO channels? IEEE Communications Magazine, 42(10), 54-59.
69. Mahmood, N. H., Alves, H., López, O. A., Shehab, M., Osorio, D. P. M., & Latva-aho, M. (2019). Six key enablers for machine type communication in 6G. arXiv preprint arXiv:1903.05406.
70. Malhotra, M., & Nair, T. (2015). Evolution of knowledge representation and retrieval techniques. International Journal of Intelligent Systems and Applications, 7(7), 18.
71. Malik, A., & Singh, P. (2015). Free space optics: current applications and future challenges. International Journal of Optics, 2015.
72. Marzetta, T. L. (2010). Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas. IEEE Transactions on Wireless Communications, 9(11), 3590-3600. doi:10.1109/twc.2010.092810.091092
73. Meyer, M. (2000). Does science push technology? Patents citing scientific literature. Research policy, 29(3), 409-434.
74. Mihalcea, R., & Tarau, P. (2004). Textrank: Bringing order into text. Paper presented at the Proceedings of the 2004 conference on empirical methods in natural language processing.
75. Mijumbi, R., Serrat, J., Gorricho, J.-L., Rubio-Loyola, J., & Davy, S. (2015). Server placement and assignment in virtualized radio access networks. Paper presented at the 2015 11th international conference on network and service management (CNSM).
76. Mishra, D., & Natalizio, E. (2020). A survey on cellular-connected UAVs: Design challenges, enabling 5G/B5G innovations, and experimental advancements. Computer Networks, 182. doi:10.1016/j.comnet.2020.107451
77. Morris, S. A., & Van der Veer Martens, B. (2008). Mapping research specialties. Annual review of information science and technology, 42(1), 213-295.
78. Mozaffari, M., Taleb Zadeh Kasgari, A., Saad, W., Bennis, M., & Debbah, M. (2019). Beyond 5G With UAVs: Foundations of a 3D Wireless Cellular Network. IEEE Transactions on Wireless Communications, 18(1), 357-372. doi:10.1109/twc.2018.2879940
79. Mukherjee, J., & Ramamurthy, B. (2012). Communication technologies and architectures for space network and interplanetary internet. IEEE communications surveys & tutorials, 15(2), 881-897.
80. Murtagh, F. (1983). A survey of recent advances in hierarchical clustering algorithms. The computer journal, 26(4), 354-359.
81. Nagpal, A., Jatain, A., & Gaur, D. (2013). Review based on data clustering algorithms. Paper presented at the 2013 IEEE conference on information & communication technologies.
82. Nawaz, S. J., Sharma, S. K., Wyne, S., Patwary, M. N., & Asaduzzaman, M. (2019). Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future. IEEE Access, 7, 46317-46350. doi:10.1109/access.2019.2909490
83. Niknam, S., Roy, A., Dhillon, H. S., Singh, S., Banerji, R., Reed, J. H., . . . Yoon, S. (2020). Intelligent O-RAN for beyond 5G and 6G wireless networks. arXiv preprint arXiv:2005.08374.
84. Pan, Y., Zheng, S., Zheng, J., Li, Y., Jin, X., Chi, H., & Zhang, X. (2016). Generation of orbital angular momentum radio waves based on dielectric resonator antenna. IEEE Antennas and Wireless Propagation Letters, 16, 385-388.
85. Patriciello, N., Lagen, S., Giupponi, L., & Bojovic, B. (2019). An Improved MAC Layer for the 5G NR ns-3 module. Paper presented at the Proceedings of the 2019 Workshop on Ns-3.
86. Peltonen, E., Bennis, M., Capobianco, M., Debbah, M., Ding, A., Gil-Castiñeira, F., . . . Kliks, A. (2020). 6G white paper on edge intelligence. arXiv preprint arXiv:2004.14850.
87. Perozzi, B., Al-Rfou, R., & Skiena, S. (2014). Deepwalk: Online learning of social representations. Paper presented at the Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining.
88. Petri, M., Moffat, A., & Wirth, A. (2014). Graph representations and applications of citation networks. Paper presented at the Proceedings of the 2014 Australasian Document Computing Symposium.
89. Promwongsa, N., Ebrahimzadeh, A., Naboulsi, D., Kianpisheh, S., Belqasmi, F., Glitho, R., . . . Alfandi, O. (2020). A comprehensive survey of the tactile internet: State-of-the-art and research directions. IEEE Communications Surveys & Tutorials.
90. Qi, J., Ding, L., & Lim, S. (2020). Ontology-based knowledge representation of urban heat island mitigation strategies. Sustainable Cities and Society, 52, 101875.
91. Rahman, M. S. (2017). Basic graph theory: Springer.
92. Rajatheva, N., Atzeni, I., Bjornson, E., Bourdoux, A., Buzzi, S., Dore, J.-B., . . . Hu, Y. (2020). White paper on broadband connectivity in 6G. arXiv preprint arXiv:2004.14247.
93. Reimers, N., & Gurevych, I. (2019). Sentence-bert: Sentence embeddings using siamese bert-networks. arXiv preprint arXiv:1908.10084.
94. Research., S. (2020). "6G: The Next Hyper-Connected Experience for All," Samsung White Paper. Retrieved from https://research.samsung.com/next-generation-communications
95. Rose, S., Engel, D., Cramer, N., & Cowley, W. (2010). Automatic keyword extraction from individual documents. Text mining: applications and theory, 1, 1-20.
96. Rost, P., Mannweiler, C., Michalopoulos, D. S., Sartori, C., Sciancalepore, V., Sastry, N., . . . Bega, D. (2017). Network slicing to enable scalability and flexibility in 5G mobile networks. IEEE Communications Magazine, 55(5), 72-79.
97. Roxin, A., Gaber, J., Wack, M., & Nait-Sidi-Moh, A. (2007). Survey of wireless geolocation techniques. Paper presented at the 2007 IEEE Globecom Workshops.
98. Saeed, N., Almorad, H., Dahrouj, H., Al-Naffouri, T. Y., Shamma, J. S., & Alouini, M.-S. (2021). Point-to-Point Communication in Integrated Satellite-Aerial 6G Networks: State-of-the-art and Future Challenges. IEEE Open Journal of the Communications Society.
99. Salton, G., & Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. Information processing & management, 24(5), 513-523.
100. Sanchez-Gonzalez, A., Heess, N., Springenberg, J. T., Merel, J., Riedmiller, M., Hadsell, R., & Battaglia, P. (2018). Graph networks as learnable physics engines for inference and control. Paper presented at the International Conference on Machine Learning.
101. Sanguinetti, L., Bjornson, E., & Hoydis, J. (2020). Toward Massive MIMO 2.0: Understanding Spatial Correlation, Interference Suppression, and Pilot Contamination. IEEE Transactions on Communications, 68(1), 232-257. doi:10.1109/tcomm.2019.2945792
102. Sarkar, S., & Maiti, J. (2020). Machine learning in occupational accident analysis: A review using science mapping approach with citation network analysis. Safety science, 131, 104900.
103. Sathya, V., Kala, S. M., Rochman, M. I., Ghosh, M., & Roy, S. (2020). Standardization advances for cellular and Wi-Fi coexistence in the unlicensed 5 and 6 GHz bands. GetMobile: Mobile Computing and Communications, 24(1), 5-15.
104. Saxena, A., Prasad, M., Gupta, A., Bharill, N., Patel, O. P., Tiwari, A., . . . Lin, C.-T. (2017). A review of clustering techniques and developments. Neurocomputing, 267, 664-681.
105. Shariatmadari, H., Ratasuk, R., Iraji, S., Laya, A., Taleb, T., Jäntti, R., & Ghosh, A. (2015). Machine-type communications: current status and future perspectives toward 5G systems. IEEE Communications Magazine, 53(9), 10-17.
106. Sharma, P., & Li, Y. (2019). Self-Supervised Contextual Keyword and Keyphrase Retrieval with Self-Labelling.
107. Sharma, P., & Tripathi, R. (2017). Patent citation: A technique for measuring the knowledge flow of information and innovation. World Patent Information, 51, 31-42.
108. Shi, P., & Lin, J. (2019). Simple bert models for relation extraction and semantic role labeling. arXiv preprint arXiv:1904.05255.
109. Siddiqi, S., & Sharan, A. (2015). Keyword and keyphrase extraction techniques: a literature review. International Journal of Computer Applications, 109(2).
110. Small, H. (1973). Co‐citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for information Science, 24(4), 265-269.
111. Small, H. (1997). Update on science mapping: Creating large document spaces. Scientometrics, 38(2), 275-293.
112. Solaija, M. S. J., Salman, H., Kihero, A. B., Sağlam, M. İ., & Arslan, H. (2021). Generalized coordinated multipoint framework for 5G and beyond. IEEE Access, 9, 72499-72515.
113. Song, M., Heo, G. E., & Lee, D. (2015). Identifying the landscape of Alzheimer’s disease research with network and content analysis. Scientometrics, 102(1), 905-927.
114. Steier, A. M., & Belew, R. K. (1993). Exporting phrases: A statistical analysis of topical language. Paper presented at the Second Symposium on Document Analysis and Information Retrieval.
115. Suresh, B., Bhat, D., & Zink, M. (2018). An evaluation of sdn and nfv support for parallel, alternative protocol stack operations. Paper presented at the 2018 IEEE International Conference on Communications (ICC).
116. Tafintsev, N., Valkama, M., Moltchanov, D., Gerasimenko, M., Gapeyenko, M., Zhu, J., . . . Koucheryavy, Y. (2020). Aerial Access and Backhaul in mmWave B5G Systems: Performance Dynamics and Optimization. IEEE Communications Magazine, 58(2), 93-99. doi:10.1109/mcom.001.1900318
117. Tang, J., Qu, M., Wang, M., Zhang, M., Yan, J., & Mei, Q. (2015). Line: Large-scale information network embedding. Paper presented at the Proceedings of the 24th international conference on world wide web.
118. Trappey, A. J., Trappey, C., Wang, W., & Hsieh, H. (2018). Patent analysis of key technologies for smart retailing and their projected economic impact. Paper presented at the 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design ((CSCWD)).
119. Trappey, A. J., Trappey, C. V., Govindarajan, U. H., & Jhuang, A. C. (2018). Construction and validation of an ontology-based technology function matrix: technology mining of cyber physical system patent portfolios. World Patent Information, 55, 19-24.
120. Trappey, C. V., Trappey, A. J., & Liu, B.-H. (2020). Identify trademark legal case precedents-Using machine learning to enable semantic analysis of judgments. World Patent Information, 62, 101980.
121. Trappey, C. V., Trappey, A. J. C., & Chen, L. W. L. (2017). Computer-supported portfolio analysis and comparison using ontology-based patent classification mapping scheme: the case of mobile communication patent pools. Cluster Computing, 20(2), 1661-1677. doi:10.1007/s10586-016-0722-2
122. Tunali, V., Bilgin, T., & Camurcu, A. (2016). An improved clustering algorithm for text mining: Multi-cluster spherical K-Means. International Arab Journal of Information Technology (IAJIT), 13(1).
123. Uschold, M., & Gruninger, M. (2004). Ontologies and semantics for seamless connectivity. ACM SIGMod Record, 33(4), 58-64.
124. Uzun, Y. (2005). Keyword extraction using naive bayes. Paper presented at the Bilkent University, Department of Computer Science, Turkey www. cs. bilkent. edu. tr/~ guvenir/courses/CS550/Workshop/Yasin_Uzun. pdf.
125. Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., . . . Polosukhin, I. (2017). Attention is all you need. Paper presented at the Advances in neural information processing systems.
126. Wang, L., & Pan, C. (2014). Robust level set image segmentation via a local correntropy-based K-means clustering. Pattern Recognition, 47(5), 1917-1925.
127. World Intellectual Property Organization. (2022a). WIPO Pearl. Retrieved from https://wipopearl.wipo.int/en/conceptmap
128. World Intellectual Property Organization. (2022b). WIPO Pearl - User Guide. Retrieved from https://www.wipo.int/reference/en/wipopearl/guide.html
129. Wu, J., Zhang, Z., Hong, Y., & Wen, Y. (2015). Cloud radio access network (C-RAN): a primer. IEEE network, 29(1), 35-41.
130. Wu, Y., Lian, D., Xu, Y., Wu, L., & Chen, E. (2020). Graph convolutional networks with markov random field reasoning for social spammer detection. Paper presented at the Proceedings of the AAAI Conference on Artificial Intelligence.
131. Xie, Q., Zhu, Y., Huang, J., Du, P., & Nie, J.-Y. (2021). Graph neural collaborative topic model for citation recommendation. ACM Transactions on Information Systems (TOIS), 40(3), 1-30.
132. Zhang, K., Xu, H., Tang, J., & Li, J. (2006). Keyword extraction using support vector machine. Paper presented at the international conference on web-age information management.
133. Zhang, L. (2011). Identifying key technologies in Saskatchewan, Canada: Evidence from patent information. World Patent Information, 33(4), 364-370.
134. Zhao, A., & Yu, Y. (2021). Knowledge-enabled BERT for aspect-based sentiment analysis. Knowledge-Based Systems, 107220.
135. Zhou, J., Cui, G., Hu, S., Zhang, Z., Yang, C., Liu, Z., . . . Sun, M. (2020). Graph neural networks: A review of methods and applications. AI Open, 1, 57-81. doi:10.1016/j.aiopen.2021.01.001
136. 徐達儒, & 許鴻基. (2015). SDN 與 NFV 相關標準與發展趨勢. 電腦與通訊(161), 64-75.