MMKG: Multi-modal Knowledge Graphs

被引:89
|
作者
Liu, Ye [1 ]
Li, Hui [2 ]
Garcia-Duran, Alberto [3 ]
Niepert, Mathias [4 ]
Onoro-Rubio, Daniel [4 ]
Rosenblum, David S. [1 ]
机构
[1] Natl Univ Singapore, Singapore, Singapore
[2] Xiamen Univ, Xiamen, Fujian, Peoples R China
[3] Ecole Polytech Fed Lausanne, Lausanne, Switzerland
[4] NEC Labs Europe, Heidelberg, Germany
来源
SEMANTIC WEB, ESWC 2019 | 2019年 / 11503卷
关键词
D O I
10.1007/978-3-030-21348-0_30
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We present Mmkg, a collection of three knowledge graphs that contain both numerical features and (links to) images for all entities as well as entity alignments between pairs of KGs. Therefore, multi-relational link prediction and entity matching communities can benefit from this resource. We believe this data set has the potential to facilitate the development of novel multi-modal learning approaches for knowledge graphs. We validate the utility of Mmkg in the sameAs link prediction task with an extensive set of experiments. These experiments show that the task at hand benefits from learning of multiple feature types.
引用
收藏
页码:459 / 474
页数:16
相关论文
共 50 条
  • [1] MMKG-PAR: Multi-Modal Knowledge Graphs-Based Personalized Attraction Recommendation
    Zhang, Gengyue
    Li, Hao
    Li, Shuangling
    Wang, Beibei
    Ding, Zhixing
    [J]. SUSTAINABILITY, 2024, 16 (05)
  • [2] Multi-modal Knowledge Graphs for Recommender Systems
    Sun, Rui
    Cao, Xuezhi
    Zhao, Yan
    Wan, Junchen
    Zhou, Kun
    Zhang, Fuzheng
    Wang, Zhongyuan
    Zheng, Kai
    [J]. CIKM '20: PROCEEDINGS OF THE 29TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT, 2020, : 1405 - 1414
  • [3] A Survey of Multi-modal Knowledge Graphs: Technologies and Trends
    Liang, Wanying
    De Meo, Pasquale
    Tang, Yong
    Zhu, Jia
    [J]. ACM Computing Surveys, 2024, 56 (11)
  • [4] Multi-modal Graph Learning over UMLS Knowledge Graphs
    Burger, Manuel
    Ratsch, Gunnar
    Kuznetsova, Rita
    [J]. MACHINE LEARNING FOR HEALTH, ML4H, VOL 225, 2023, 225 : 52 - 81
  • [5] MMIEA: Multi-modal Interaction Entity Alignment model for knowledge graphs
    Zhu, Bin
    Wu, Meng
    Hong, Yunpeng
    Chen, Yi
    Xie, Bo
    Liu, Fei
    Bu, Chenyang
    Ding, Weiping
    [J]. INFORMATION FUSION, 2023, 100
  • [6] Multi-modal knowledge graphs enhance patient stratification & biomarker discovery
    Goncalves, Miguel
    Cohen-Setton, Jake
    Kagiampakis, Ioannis
    Sidders, Ben
    Bulusu, Krishna
    [J]. CANCER RESEARCH, 2024, 84 (06)
  • [7] Fusion of Multi-Modal Underwater Ship Inspection Data with Knowledge Graphs
    Hirsch, Joseph
    Elvesaeter, Brian
    Cardaillac, Alexandre
    Bauer, Bernhard
    Waszak, Maryna
    [J]. 2022 OCEANS HAMPTON ROADS, 2022,
  • [8] MultiJAF: Multi-modal joint entity alignment framework for multi-modal knowledge graph
    Cheng, Bo
    Zhu, Jia
    Guo, Meimei
    [J]. NEUROCOMPUTING, 2022, 500 : 581 - 591
  • [9] Multi-Modal Curriculum Learning over Graphs
    Gong, Chen
    Yang, Jian
    Tao, Dacheng
    [J]. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2019, 10 (04)
  • [10] Systematic Literature Review on Knowledge Graphs in Construction Management from a Multi-Modal Perspective
    Zhang, Jingqi
    Jiang, Shaohua
    [J]. INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION, 2024,