Article
Mathematics, Applied
Marta Borowiecka-Olszewska, Ewa Drgas-Burchardt, Nahid Yelene Javier-Nol, Rita Zuazua
Summary: The study focuses on arc colourings of oriented graphs, proving the existence of such colouring being an NP-complete problem and proposing the conjecture that there exists a consecutive colourable orientation for each graph, with verifications done on specific classes of graphs.
RESULTS IN MATHEMATICS
(2021)
Article
Mathematics, Applied
Sakander Hayat, Hafiz Muhammad Afzal Siddiqui, Muhammad Imran, Hafiz Muhammad Ikhlaq, Jinde Cao
Summary: This study extends previous research on the properties of certain basic directed graph families to include more non-trivial graph structures. It also investigates the change in propagation time when the orientation of one edge is flipped.
Article
Mathematics
Z. Stanic
Summary: In this paper, we investigate oriented and signed graphs that have the same spectrum but are not switching isomorphic, referred to as cospectral graphs. We prove that there is a bijective correspondence between cospectral bipartite oriented graphs and cospectral bipartite signed graphs. Various constructions of cospectral oriented (signed) graphs are also provided, including infinite families of cospectral regular signed graphs and cospectral bipartite regular oriented graphs. Particularly, we discuss the relations between cospectral oriented graphs and cospectral signed graphs.
LINEAR & MULTILINEAR ALGEBRA
(2022)
Article
Physics, Mathematical
Sergei Merkulov, Marko Zivkovic
Summary: We prove that the action of the Grothendieck-Teichmuller group on the genus completed properad of (homotopy) Lie bialgebras commutes with the reversing directions involution of the latter. We also prove that every universal quantization of Lie bialgebras is homotopy equivalent to the one which commutes with the duality involution exchanging Lie bracket and Lie cobracket. The proofs are based on a new result in the theory of oriented graph complexes (which can be of independent interest) saying that the involution on an oriented graph complex that changes all directions on edges induces the identity map on its cohomology.
LETTERS IN MATHEMATICAL PHYSICS
(2022)
Article
Mathematics, Applied
Zoran Stanic
Summary: This passage discusses the association between oriented graphs and signed graphs, proving that they are mutually associated when the underlying graph is bipartite. Based on this result, it is shown that in the bipartite case, the skew spectrum of G' can be obtained from the spectrum of an associated signed graph G, and vice versa. In the non-bipartite case, it is proved that the skew spectrum of G' can be obtained from the spectrum of a signed graph associated with the bipartite double of G. Thus, the theory of skew spectra of oriented graphs is shown to have a strong relationship with the theory of spectra of signed graphs, and some problems concerning oriented graphs can be considered within the framework of signed graphs.
LINEAR ALGEBRA AND ITS APPLICATIONS
(2023)
Article
Mathematics
Sandip Das, Prantar Ghosh, Shamik Ghosh, Sagnik Sen
Summary: This paper focuses on oriented bipartite graphs, introducing the concept of bitransitive graphs and exploring their various characterizations. The study also delves into acyclic bitournaments and their equivalence to bitransitive bitournaments. Furthermore, the paper touches on the Caccetta-Haggkvist Conjecture in oriented bipartite graphs and introduces the concept of odd-even graphs in relation to bipartite graphs. Finally, the study observes Hamiltonian properties of odd-even graphs related to Goldbach graphs for a small number of vertices.
DISCRETE MATHEMATICS
(2021)
Article
Computer Science, Information Systems
Yonghui Xu, Shengjie Sun, Huiguo Zhang, Chang'an Yi, Yuan Miao, Dong Yang, Xiaonan Meng, Yi Hu, Ke Wang, Huaqing Min, Hengjie Song, Chuanyan Miao
Summary: This article presents a Robustly Time-aware Graph Embedding (RTGE) method that incorporates temporal smoothness, aimed at improving the performance of knowledge graph embedding by considering temporal information. The proposed method integrates a measure of temporal smoothness in the learning process and provides a task-oriented negative sampling strategy associated with temporally aware information to enhance adaptability and achieve superior performance in various tasks. Experimental results demonstrate the effectiveness of RTGE in entity/relationship/temporal scoping prediction tasks.
ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA
(2022)
Article
Computer Science, Artificial Intelligence
Taher Hekmatfar, Saman Haratizadeh, Sama Goliaei
Summary: In this paper, we propose PGRec, a novel model-based ranking-oriented recommendation framework that extracts vector representations from PrefGraph to predict user preferences and generate recommendation lists. Experimental results show that PGRec outperforms other model-based and neighborhood-based recommendation algorithms in terms of the NDCG metric.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Yuhang Chang, Wei Zhou, Junhao Wen
Summary: This paper proposes a novel multirelational recommendation model IHG4MR, which utilizes user characteristics and graph structure to split users and build multiple interactive graphs to mitigate the oversmoothing problem. Experimental results show that IHG4MR outperforms existing models, demonstrating its effectiveness in multirelational recommendation.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Bin Zhou, Bao Hua, Xinghai Gu, Yuqian Lu, Tao Peng, Yu Zheng, Xingwang Shen, Jinsong Bao
Summary: The study proposes an end-to-end industrial tabular information extraction and semantic fusion method to help the manufacturing sector convert unstructured data into structured knowledge and guide cognitive intelligence analysis. By integrating text and tabular information, a tabular information-oriented causality event evolutionary knowledge graph is constructed, and an entity alignment approach is designed to fuse cross-knowledge graphs into a unified knowledge base.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Xiaojuan Zhao, Yan Jia, Aiping Li, Rong Jiang, Kai Chen, Ye Wang
Summary: This work introduces a target relational attention-oriented reasoning model in knowledge graph reasoning, which uses hierarchical attention mechanism to improve node-embedding representation and alleviate over-smoothing. Experiments demonstrate significant outperformance over current state-of-the-art methods, and the study on encoder parameters reveals ways to enhance model performance.
Article
Automation & Control Systems
Luyi Bai, Xiangnan Ma, Xiangxi Meng, Xin Ren, Yujing Ke
Summary: In recent years, there has been an increased need for completing temporal knowledge graphs (TKGs) which associate time information with each event. Existing efforts have extended static knowledge graph completion models to handle time-dependent representations and have encoded the structural information of events. However, these efforts often focus on entity features and do not explore the power of relations for TKG completion.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Shi-Xue Zhang, Xiaobin Zhu, Jie-Bo Hou, Xu-Cheng Yin
Summary: In this study, we propose a graph fusion network called GFNet for multi-oriented object detection. By utilizing a locality-aware clustering algorithm and graph convolutional network (GCN), GFNet adaptively fuses dense detection boxes to detect more accurate and holistic multi-oriented object instances.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Ruowang Yu, Yu Xin, Yihong Dong, Jiangbo Qian
Summary: Graph data mining is an important method for managing complex systems in AI. Node classification, as a branch of graph data mining, has wide applications in paper and user classification in different networks. This research proposes a GSSC model that includes a learnable node-structure feature, sampler, encoder, and classifier to obtain structural embeddings that better reflect the topological structure of non-attribute graphs. Experimental results show that our GSSC model outperforms other methods in node classification for graphs without node attributes.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Acoustics
Tongzhou Ye, Tianhao Peng, Jingzhao Li
Summary: This paper proposes an equipment sound frequency ridges positioning model (HVDG-RSAGE model) which uses the Horizontal Visibility Directed Graph and Resampling graph Sampling and Aggregate embedding model to identify the position of equipment frequency ridges. The experiments show that this model improves the accuracy of equipment sound frequency ridges positioning.
JOURNAL OF VIBRATION AND CONTROL
(2023)