Literatura científica selecionada sobre o tema "Knowledge Graph (KG)"
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Artigos de revistas sobre o assunto "Knowledge Graph (KG)"
Hao, Wu, Jiao Menglin, Tian Guohui, Ma Qing e Liu Guoliang. "R-KG: A Novel Method for Implementing a Robot Intelligent Service". AI 1, n.º 1 (2 de março de 2020): 117–40. http://dx.doi.org/10.3390/ai1010006.
Texto completo da fonteKhan, Arijit. "Knowledge Graphs Querying". ACM SIGMOD Record 52, n.º 2 (10 de agosto de 2023): 18–29. http://dx.doi.org/10.1145/3615952.3615956.
Texto completo da fonteBai, Liting, Lin Liu, Shengli Song e Yueshen Xu. "NCR-KG: news community recommendation with knowledge graph". CCF Transactions on Pervasive Computing and Interaction 1, n.º 4 (11 de novembro de 2019): 250–59. http://dx.doi.org/10.1007/s42486-019-00020-3.
Texto completo da fonteFang, Yin, Qiang Zhang, Haihong Yang, Xiang Zhuang, Shumin Deng, Wen Zhang, Ming Qin, Zhuo Chen, Xiaohui Fan e Huajun Chen. "Molecular Contrastive Learning with Chemical Element Knowledge Graph". Proceedings of the AAAI Conference on Artificial Intelligence 36, n.º 4 (28 de junho de 2022): 3968–76. http://dx.doi.org/10.1609/aaai.v36i4.20313.
Texto completo da fonteTong, Peihao, Qifan Zhang e Junjie Yao. "Leveraging Domain Context for Question Answering Over Knowledge Graph". Data Science and Engineering 4, n.º 4 (4 de novembro de 2019): 323–35. http://dx.doi.org/10.1007/s41019-019-00109-w.
Texto completo da fonteTian, Xin, e Yuan Meng. "Relgraph: A Multi-Relational Graph Neural Network Framework for Knowledge Graph Reasoning Based on Relation Graph". Applied Sciences 14, n.º 7 (8 de abril de 2024): 3122. http://dx.doi.org/10.3390/app14073122.
Texto completo da fonteYan, Yuchen, Lihui Liu, Yikun Ban, Baoyu Jing e Hanghang Tong. "Dynamic Knowledge Graph Alignment". Proceedings of the AAAI Conference on Artificial Intelligence 35, n.º 5 (18 de maio de 2021): 4564–72. http://dx.doi.org/10.1609/aaai.v35i5.16585.
Texto completo da fonteKejriwal, Mayank. "Knowledge Graphs: A Practical Review of the Research Landscape". Information 13, n.º 4 (23 de março de 2022): 161. http://dx.doi.org/10.3390/info13040161.
Texto completo da fonteZuo, H., Y. Yin e P. Childs. "Patent-KG: Patent Knowledge Graph Extraction for Engineering Design". Proceedings of the Design Society 2 (maio de 2022): 821–30. http://dx.doi.org/10.1017/pds.2022.84.
Texto completo da fonteBellomarini, Luigi, Marco Benedetti, Andrea Gentili, Davide Magnanimi e Emanuel Sallinger. "KG-Roar: Interactive Datalog-Based Reasoning on Virtual Knowledge Graphs". Proceedings of the VLDB Endowment 16, n.º 12 (agosto de 2023): 4014–17. http://dx.doi.org/10.14778/3611540.3611609.
Texto completo da fonteTeses / dissertações sobre o assunto "Knowledge Graph (KG)"
Salehpour, Masoud. "High-performance Query Processing over Knowledge Graphs". Thesis, The University of Sydney, 2022. https://hdl.handle.net/2123/28569.
Texto completo da fonteSima, Xingyu. "La gestion des connaissances dans les petites et moyennes entreprises : un cadre adapté et complet". Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. http://www.theses.fr/2024TLSEP047.
Texto completo da fonteKnowledge is vital for organizations, particularly in today’s Industry 4.0 context. Knowledge Management (KM) plays a critical role in an organization's success. Although KM has been relatively well-studied in large organizations, Small and Medium-sized Enterprises (SMEs) receive less attention. SMEs face unique challenges in KM, requiring a tailored KM framework. Our study aims to define a framework addressing their challenges while leveraging their inherent strengths. This thesis presents a dedicated and comprehensive SME KM framework, offering dedicated solutions from knowledge acquisition and representation to exploitation: (1) a dedicated knowledge acquisition process based on the Scrum framework, an agile methodology, (2) a dedicated knowledge representation model based on semi-structured KG, and (3) a dedicated knowledge exploitation process based on knowledge-relatedness RS. This research was conducted in collaboration with Axsens-bte, an SME specializing in consultancy and training. The partnership with Axsens-bte has provided invaluable insights and practical experiences, contributing to developing the proposed KM framework and highlighting its relevance and applicability in real-world SME contexts
Saxena, Apoorv Umang. "Leveraging KG Embeddings for Knowledge Graph Question Answering". Thesis, 2023. https://etd.iisc.ac.in/handle/2005/6082.
Texto completo da fonteOjha, Prakhar. "Utilizing Worker Groups And Task Dependencies in Crowdsourcing". Thesis, 2017. http://etd.iisc.ac.in/handle/2005/4265.
Texto completo da fonteCapítulos de livros sobre o assunto "Knowledge Graph (KG)"
Krause, Franz, Kabul Kurniawan, Elmar Kiesling, Jorge Martinez-Gil, Thomas Hoch, Mario Pichler, Bernhard Heinzl e Bernhard Moser. "Leveraging Semantic Representations via Knowledge Graph Embeddings". In Artificial Intelligence in Manufacturing, 71–85. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-46452-2_5.
Texto completo da fonteSanou, Gaoussou, Véronique Giudicelli, Nika Abdollahi, Sofia Kossida, Konstantin Todorov e Patrice Duroux. "IMGT-KG: A Knowledge Graph for Immunogenetics". In The Semantic Web – ISWC 2022, 628–42. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-19433-7_36.
Texto completo da fonteWu, Tianxing, Cong Gao, Guilin Qi, Lei Zhang, Chuanqi Dong, He Liu e Du Zhang. "KG-Buddhism: The Chinese Knowledge Graph on Buddhism". In Semantic Technology, 259–67. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70682-5_17.
Texto completo da fonteMöller, Cedric. "Knowledge Graph Population with Out-of-KG Entities". In The Semantic Web: ESWC 2022 Satellite Events, 199–214. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11609-4_35.
Texto completo da fonteKwapong, Benjamin, Amartya Sen e Kenneth K. Fletcher. "ELECTRA-KG: A Transformer-Knowledge Graph Recommender System". In Services Computing – SCC 2022, 56–70. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-23515-3_5.
Texto completo da fontePflueger, Maximilian, David J. Tena Cucala e Egor V. Kostylev. "GNNQ: A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs". In The Semantic Web – ISWC 2022, 481–97. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-19433-7_28.
Texto completo da fonteMotger, Quim, Xavier Franch e Jordi Marco. "MApp-KG: Mobile App Knowledge Graph for Document-Based Feature Knowledge Generation". In Lecture Notes in Business Information Processing, 129–37. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-61000-4_15.
Texto completo da fonteMeyer, Lars-Peter, Claus Stadler, Johannes Frey, Norman Radtke, Kurt Junghanns, Roy Meissner, Gordian Dziwis, Kirill Bulert e Michael Martin. "LLM-assisted Knowledge Graph Engineering: Experiments with ChatGPT". In Informatik aktuell, 103–15. Wiesbaden: Springer Fachmedien Wiesbaden, 2024. http://dx.doi.org/10.1007/978-3-658-43705-3_8.
Texto completo da fonteDessì, Danilo, Francesco Osborne, Diego Reforgiato Recupero, Davide Buscaldi, Enrico Motta e Harald Sack. "AI-KG: An Automatically Generated Knowledge Graph of Artificial Intelligence". In Lecture Notes in Computer Science, 127–43. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-62466-8_9.
Texto completo da fonteAnand, Avinash, Mohit Gupta, Kritarth Prasad, Ujjwal Goel, Naman Lal, Astha Verma e Rajiv Ratn Shah. "KG-CTG: Citation Generation Through Knowledge Graph-Guided Large Language Models". In Big Data and Artificial Intelligence, 37–49. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-49601-1_3.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Knowledge Graph (KG)"
Wei, Xing, e Jiangjiang Liu. "Effects of Nonlinear Functions on Knowledge Graph Convolutional Networks for Recommender Systems with Yelp Knowledge Graph". In 11th International Conference on Computer Science and Information Technology (CCSIT 2021). AIRCC Publishing Corporation, 2021. http://dx.doi.org/10.5121/csit.2021.110715.
Texto completo da fonteRistoski, Petar, Zhizhong Lin e Qunzhi Zhou. "KG-ZESHEL: Knowledge Graph-Enhanced Zero-Shot Entity Linking". In K-CAP '21: Knowledge Capture Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3460210.3493549.
Texto completo da fonteChen, Mingyang, Wen Zhang, Zhen Yao, Xiangnan Chen, Mengxiao Ding, Fei Huang e Huajun Chen. "Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting". In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/273.
Texto completo da fonteWei, Jiaqi, Shuo Han e Lei Zou. "VISION-KG: Topic-centric Visualization System for Summarizing Knowledge Graph". In WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3336191.3371863.
Texto completo da fonteQiu, Yuchen, Yuanyuan Qiao, Shuo Yang e Jie Yang. "Tax-KG: Taxation Big Data Visualization System for Knowledge Graph". In 2020 IEEE 5th International Conference on Signal and Image Processing (ICSIP). IEEE, 2020. http://dx.doi.org/10.1109/icsip49896.2020.9339403.
Texto completo da fonteCai, Jinglun, Mingda Li, Ziyan Jiang, Eunah Cho, Zheng Chen, Yang Liu, Xing Fan e Chenlei Guo. "KG-ECO: Knowledge Graph Enhanced Entity Correction For Query Rewriting". In ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2023. http://dx.doi.org/10.1109/icassp49357.2023.10096826.
Texto completo da fonteLiu, Shuwen, Bernardo Cuenca Grau, Ian Horrocks e Egor V. Kostylev. "Revisiting Inferential Benchmarks for Knowledge Graph Completion". In 20th International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/kr.2023/45.
Texto completo da fonteHuang, Yu-Xuan, Zequn Sun, Guangyao Li, Xiaobin Tian, Wang-Zhou Dai, Wei Hu, Yuan Jiang e Zhi-Hua Zhou. "Enabling Abductive Learning to Exploit Knowledge Graph". In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/427.
Texto completo da fonteWu, Zhanglin, Min Zhang, Ming Zhu, Yinglu Li, Ting Zhu, Hao Yang, Song Peng e Ying Qin. "KG-BERTScore: Incorporating Knowledge Graph into BERTScore for Reference-Free Machine Translation Evaluation". In IJCKG 2022: 11th International Joint Conference On Knowledge Graphs. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3579051.3579065.
Texto completo da fonteTu, Yamei, Rui Qiu e Han-Wei Shen. "KG-PRE-view: Democratizing a TVCG Knowledge Graph through Visual Explorations". In 2024 IEEE 17th Pacific Visualization Conference (PacificVis). IEEE, 2024. http://dx.doi.org/10.1109/pacificvis60374.2024.00026.
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