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Robustness-via-synthesis: Robust training with generative adversarial perturbations. Neurocomputing 2023. [DOI: 10.1016/j.neucom.2022.10.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Wu T, Yang N, Chen L, Xiao X, Xian X, Liu J, Qiao S, Cui C. ERGCN: Data enhancement-based robust graph convolutional network against adversarial attacks. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.10.115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Khobragade AR, Ghumbre SU. Study and analysis of various link predictions in knowledge graph: A challenging overview. INTELLIGENT DECISION TECHNOLOGIES 2022. [DOI: 10.3233/idt-210103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Knowledge Graph (KG) is the network which contains some topic-based entities, called nodes, and the associated information among the entities. Here, the concept in the knowledge graph is denoted by the tuple relationship, such that the ⟨entity1, predicate, entity2⟩. The entity in the knowledge graph is the abstract concepts based on the particular object, namely the organization, dataset, people, and some associated documentation. The big issue in the KG is that it consists of some incomplete information. The missing details can be identified by employing the knowledge graph completion (KGC) solution. KGC is the same as the link prediction concepts in the knowledge graphs. However, this concept is more complex that it does not predict the link relationship among the nodes but also the diversified information from the link relations. Hence this survey analyzes different methods of link prediction techniques, and this review provides a detailed review of 50 research papers concentrating on various methods, like embedding-based methods, deep learning methods, knowledge acquisition methods, ranking methods, and representation learning methods. The analysis is carried out with respect to the survey based on the publication year, research techniques, performance measures, dataset, toolset and achievement of the research methodologies. Also, the problems in the methods are explained in the research gaps and issues. Furthermore, the future extent of these research works is done based on the limitations identified from the existing research methods.
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Affiliation(s)
| | - Shashikant U. Ghumbre
- Government College of Engineering and Research, Avasari Khurd, Savitribai Phule Pune University, Pune, India
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Liu L, Du Y, Wang Y, Cheung WK, Zhang Y, Liu Q, Wang G. LRP2A: Layer-wise Relevance Propagation based Adversarial attacking for Graph Neural Networks. Knowl Based Syst 2022. [DOI: 10.1016/j.knosys.2022.109830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Tang R, Jiang S, Chen X, Wang W, Wang W. Network structural perturbation against interlayer link prediction. Knowl Based Syst 2022. [DOI: 10.1016/j.knosys.2022.109095] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Wu T, Wang X, Qiao S, Xian X, Liu Y, Zhang L. Small perturbations are enough: Adversarial attacks on time series prediction. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2021.11.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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Poisoning attacks against knowledge graph-based recommendation systems using deep reinforcement learning. Neural Comput Appl 2021. [DOI: 10.1007/s00521-021-06573-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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