Maximizing influence via link prediction in evolving networks by Kexin Zhang, Mo Li, Shuang Teng, Lingling Li, Yi Wang, Xuezhuan Zhao, Jinhong Di, Ji Zhang

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Development and investigation of parallel model of bee colony algorithms for cryptanalysis problem solving by Yury O Chernyshev, Alexander S Sergeev, Alexander N Ryazanov, Evgeny O. Dubrov

“…Research Results . Theoretical estimates of time complexity of the bee colony algorithm are given as the key data. …”
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Dual-branch graph Transformer for node classification by Yong Zhang, Jingjing Song, Eric C.C. Tsang, Yingxing Yu

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Methodology for Building a Prototype System for Complex Data Analysis of Thematic Sites by I. I. Piletski, M. P. Batura, N. A. Volarava

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Smart City Traffic Flow and Signal Optimization Using STGCN-LSTM and PPO Algorithms by Tuxiang Lin, Rongliang Lin

“…This study presents a novel framework that integrates the Spatiotemporal Graph Convolutional Network-Long Short-Term Memory (STGCN-LSTM) model for traffic flow prediction with the Proximal Policy Optimization (PPO) algorithm for dynamic traffic signal control. …”
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Unveiling optimal SDG pathways: an innovative automated recommendation approach integrating graph pruning, intent graph, and attention mechanism by Qiang Wang, Zhihang Yu, Shu Wang, Yunqiang Zhu, Xiaoliang Dai, Zhiqiang Zou, Weiming Huang, Christophe Claramunt

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COMPACT PARTITIONS ON LARGE DIMENSION TOPOLOGICAL GRAPHS by Alexander V. Pogrebnoy, Andrey V. Pogrebnoy

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Detecting anomalies in graph networks on digital markets. by Agata Skorupka

“…It compares different graph algorithms to extract feature sets for anomaly detection models. …”
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Graph-based method for constructing consensus trees by Torquet Elio, Jansson Jesper, Tahiri Nadia

“…In this paper, we extend PrimConsTree, an graph-based method for constructing consensus trees. …”
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Investigation of multimorbidity patterns and association rules in patients with type 2 diabetes mellitus using association rules mining algorithm by Lianhua Liu, Xiaodan Wang, Mei Gui, Feng Ju, Li Cao, Bo Bi

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Applications of mathematical programming in graceful labeling of graphs by Kourosh Eshghi, Parham Azimi

“…Graceful labeling is one of the best known labeling methods of graphs. Despite the large number of papers published on the subject of graph labeling, there are few particular techniques to be used by researchers to gracefully label graphs. …”
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Design and application research of traditional Chinese medicine teaching resource recommendation system based on multivariate data mining driven algorithm by Wei Zhang, Yaqing Liu, Qiang Zhang, Xiaomin Chen

“…The study uses a hybrid recommendation algorithm, combines collaborative filtering with content filtering, and integrates it into the knowledge graph of traditional Chinese medicine to realize in-depth data mining. …”
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Offline System for 2D Indoor Navigation Utilizing Advanced Data Structures by Jorge Luis Veloz, Leo Sebastián Intriago, Jean Carlos Palma, Andrea Katherine Alcívar-Cedeño, Álvaro Antón-Sacho, Pablo Fernández-Arias, Edwan Anderson Ariza, Diego Vergara

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Survey on explainable knowledge graph reasoning methods by Yi XIA, Mingjng LAN, Xiaohui CHEN, Junyong LUO, Gang ZHOU, Peng HE

“…In recent years, deep learning models have achieved remarkable progress in the prediction and classification tasks of artificial intelligence systems.However, most of the current deep learning models are black box, which means it is not conducive to human cognitive reasoning process.Meanwhile, with the continuous breakthroughs of artificial intelligence in the researches and applications, high-performance complex algorithms, models and systems generally lack the transparency and interpretability of decision making.This makes it difficult to apply the technologies in a wide range of fields requiring strict interpretability, such as national defense, medical care and cyber security.Therefore, the interpretability of artificial intelligence should be integrated into these algorithms and systems in the process of knowledge reasoning.By means of carrying out explicit explainable intelligence reasoning based on discrete symbolic representation and combining technologies in different fields, a behavior explanation mechanism can be formed which is an important way for artificial intelligence to realize data perception to intelligence perception.A comprehensive review of explainable knowledge graph reasoning was given.The concepts of explainable artificial intelligence and knowledge reasoning were introduced briefly.The latest research progress of explainable knowledge graph reasoning methods based on the three paradigms of artificial intelligence was introduced.Specifically, the ideas and improvement process of the algorithms in different scenarios of explainable knowledge graph reasoning were explained in detail.Moreover, the future research direction and the prospect of explainable knowledge graph reasoning were discussed.…”
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Effectiveness of Partition and Graph Theoretic Clustering Algorithms for Multiple Source Partial Discharge Pattern Classification Using Probabilistic Neural Network and Its Adaptiv... by S. Venkatesh, S. Gopal, K. Kannan

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Blockchain digital forensics: technology and architecture by FAN Wei, LI Haibo, ZHANG Zhujun

“…This framework integrated evidence information into the on-chain data structure and introduced a complementary graph analysis algorithm to standardize evidence collection across various scenarios. …”
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The electromagnetic transient simulation acceleration algorithm based on delay mitigation of dynamic critical paths by Qi Guo, Yuanhong Lu, Jie Zhang, Jingyue Zhang, Libin Huang, Haiping Guo, Tianyu Guo, Liang Tu

“…In this paper, building upon existing scheduling algorithms, we introduce a static task scheduling algorithm based on directed acyclic graphs. …”
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Metropolitan Area Network Model Design Algorithm Using Regional Railways Information and Daily Movement Data for Beyond 5G Research by Koga Nakamura, Shotaro Kitano, Yusuke Hirota, Takehiro Tsuritani, Hiroshi Hasegawa, Takuji Tachibana

“…The designed MAN models are a simple plane graph and are widely used in numerous research domains. …”
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Visualization of Anomalies using Graph-Based Anomaly Detection by Ramesh Paudel, Lauren Tharp, Dulce Kaiser, William Eberle, Gerald Gannod

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Research on Random Access Technology of Inter-Frame Interference Cancellation for 6G Satellite Internet of Things by Yu XU, Qing GUO

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