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Готові списки джерел за темами / Graph-type classification / Статті в журналах

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Статті в журналах з теми "Graph-type classification"

Автор: Grafiati

Опубліковано: 3 червня 2025

Оновлено: 31 липня 2025

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1

Perepelitsa, V. A., I. V. Kozin, and S. V. Kurapov. "Methods of classification and algorithms of graph coloring." Researches in Mathematics 16 (February 7, 2021): 135. http://dx.doi.org/10.15421/240816.

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We study the connection between classifications on finite set and the problem of graph coloring. We consider the optimality criterion for classification of special type: h-classifications, which are built on the base of proximity measure. It is shown that the problem of finding the optimal h-classification can be reduced to the problem of coloring of non-adjacency graph vertices by the smallest possible number of colors. We consider algorithms of proper coloring of graph vertices.

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2

Gharaee, Zahra, Shreyas Kowshik, Oliver Stromann, and Michael Felsberg. "Graph representation learning for road type classification." Pattern Recognition 120 (December 2021): 108174. http://dx.doi.org/10.1016/j.patcog.2021.108174.

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3

Yang, Dilian. "Factoriality and Type Classification of k-Graph von Neumann Algebras." Proceedings of the Edinburgh Mathematical Society 60, no. 2 (2016): 499–518. http://dx.doi.org/10.1017/s0013091516000304.

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AbstractLet be a single vertex k-graph and let be the von Neumann algebra induced from the Gelfand–Naimark–Segal (GNS) representation of a distinguished state ω of its k-graph C*-algebra . In this paper we prove the factoriality of , and furthermore determine its type when either has the little pullback property, or the intrinsic group of has rank 0. The key step to achieving this is to show that the fixed-point algebra of the modular action corresponding to ω has a unique tracial state.

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4

Power, Stephen C., Igor A. Baburin, and Davide M. Proserpio. "Isotopy classes for 3-periodic net embeddings." Acta Crystallographica Section A Foundations and Advances 76, no. 3 (2020): 275–301. http://dx.doi.org/10.1107/s2053273320000625.

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Entangled embedded periodic nets and crystal frameworks are defined, along with their dimension type, homogeneity type, adjacency depth and periodic isotopy type. Periodic isotopy classifications are obtained for various families of embedded nets with small quotient graphs. The 25 periodic isotopy classes of depth-1 embedded nets with a single-vertex quotient graph are enumerated. Additionally, a classification is given of embeddings of n-fold copies of pcu with all connected components in a parallel orientation and n vertices in a repeat unit, as well as demonstrations of their maximal symmet

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5

Wang, Zijian, Rafael Sacks, and Timson Yeung. "Exploring graph neural networks for semantic enrichment: Room type classification." Automation in Construction 134 (February 2022): 104039. http://dx.doi.org/10.1016/j.autcon.2021.104039.

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6

Rowland, Dana. "Classification of book representations of K6." Journal of Knot Theory and Its Ramifications 26, no. 12 (2017): 1750075. http://dx.doi.org/10.1142/s0218216517500754.

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A book representation of a graph is a particular way of embedding a graph in three-dimensional space so that the vertices lie on a circle and the edges are chords on disjoint topological disks. We describe a set of operations on book representations that preserves ambient isotopy, and apply these operations to [Formula: see text], the complete graph with six vertices. We prove there are exactly 59 distinct book representations for [Formula: see text], and we identify the number and type of knotted and linked cycles in each representation. We show that book representations of [Formula: see text

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7

Dong, Guozhong, Weizhe Zhang, Rahul Yadav, Xin Mu, and Zhili Zhou. "OWGC-HMC: An Online Web Genre Classification Model Based on Hierarchical Multilabel Classification." Security and Communication Networks 2022 (March 29, 2022): 1–9. http://dx.doi.org/10.1155/2022/7549880.

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Web genre plays an important role in focused crawling, web link analysis, and contextual advertising. In this paper, web genre is defined as the functional purpose and the information type contained in the website. The intelligent classification of web genre can predict the content and functional type of website. However, there are several critical challenges to solve the web genre classification problem: lack of web genre classification dataset and efficient web genre classification mechanism. To improve web genre classification performance, we crawled Chinese websites of different web genres

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8

Chen, Yang, Zhonglin Ye, Haixing Zhao, and Ying Wang. "Feature-Based Graph Backdoor Attack in the Node Classification Task." International Journal of Intelligent Systems 2023 (February 21, 2023): 1–13. http://dx.doi.org/10.1155/2023/5418398.

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Graph neural networks (GNNs) have shown significant performance in various practical applications due to their strong learning capabilities. Backdoor attacks are a type of attack that can produce hidden attacks on machine learning models. GNNs take backdoor datasets as input to produce an adversary-specified output on poisoned data but perform normally on clean data, which can have grave implications for applications. Backdoor attacks are under-researched in the graph domain, and almost existing graph backdoor attacks focus on the graph-level classification task. To close this gap, we propose

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9

Li, Yiyan, Xiaomin Lu, Haowen Yan, Wenning Wang, and Pengbo Li. "A Skeleton-Line-Based Graph Convolutional Neural Network for Areal Settlements’ Shape Classification." Applied Sciences 12, no. 19 (2022): 10001. http://dx.doi.org/10.3390/app121910001.

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Among the geographic elements, shape recognition and classification is one of the im portant elements of map cartographic generalization, and the shape classification of an areal settlement is an important part of geospatial vector data. However, there is currently no relatively simple and efficient way to achieve areal settlement classification. Therefore, we combined the skeleton line vector data of an areal settlement and the graph convolutional neural network to propose an areal settlement shape classification method that (1) extracts the skeleton line of the areal settlement to form a dua

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10

TAO, PENG, CAO WENLI, CHEN JIA, et al. "Research on fabric classification based on graph neural network." Industria Textila 74, no. 01 (2023): 3–11. http://dx.doi.org/10.35530/it.074.01.202224.

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Fabric classification plays a crucial role in the modern textile industry and fashion market. In the early stage, traditional neural network methods were adopted to identify fabrics with the drawback of restricted fabric type and poor accuracy. Combining multi-frame temporality and analysing fabric graph data made from fabric motion features, this paper proposes a novel hybrid model that introduces the concept of graph networks to classify 30 textile materials in a public database. We utilize the graph inductive representation learning method (GraphSAGE, Graph Sample and Aggregate) to extract

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11

Bongini, Pietro, Niccolò Pancino, Asma Bendjeddou, Franco Scarselli, Marco Maggini, and Monica Bianchini. "Composite Graph Neural Networks for Molecular Property Prediction." International Journal of Molecular Sciences 25, no. 12 (2024): 6583. http://dx.doi.org/10.3390/ijms25126583.

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Graph Neural Networks have proven to be very valuable models for the solution of a wide variety of problems on molecular graphs, as well as in many other research fields involving graph-structured data. Molecules are heterogeneous graphs composed of atoms of different species. Composite graph neural networks process heterogeneous graphs with multiple-state-updating networks, each one dedicated to a particular node type. This approach allows for the extraction of information from s graph more efficiently than standard graph neural networks that distinguish node types through a one-hot encoded t

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12

Eilers, Søren, Gunnar Restorff, Efren Ruiz, and Adam P. W. Sørensen. "Geometric Classification of Graph C*-algebras over Finite Graphs." Canadian Journal of Mathematics 70, no. 2 (2018): 294–353. http://dx.doi.org/10.4153/cjm-2017-016-7.

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AbstractWe address the classification problem for graph C*-algebras of finite graphs (finitely many edges and vertices), containing the class of Cuntz-Krieger algebras as a prominent special case. Contrasting earlier work, we do not assume that the graphs satisfy the standard condition (K), so that the graph C*-algebras may come with uncountably many ideals.We find that in this generality, stable isomorphism of graph C*-algebras does not coincide with the geometric notion of Cuntz move equivalence. However, adding a modest condition on the graphs, the two notions are proved to be mutually equi

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13

Williams, Gerald. "Fibonacci Type Semigroups." Algebra Colloquium 21, no. 04 (2014): 647–52. http://dx.doi.org/10.1142/s1005386714000595.

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We study “Fibonacci type” groups and semigroups. By establishing asphericity of their presentations we show that many of the groups are infinite. We combine this with Adjan graph techniques and the classification of the finite Fibonacci semigroups (in terms of the finite Fibonacci groups) to extend it to the Fibonacci type semigroups.

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14

Yang, Tianchi, Linmei Hu, Chuan Shi, Houye Ji, Xiaoli Li, and Liqiang Nie. "HGAT: Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification." ACM Transactions on Information Systems 39, no. 3 (2021): 1–29. http://dx.doi.org/10.1145/3450352.

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Short text classification has been widely explored in news tagging to provide more efficient search strategies and more effective search results for information retrieval. However, most existing studies, concentrating on long text classification, deliver unsatisfactory performance on short texts due to the sparsity issue and the insufficiency of labeled data. In this article, we propose a novel heterogeneous graph neural network-based method for semi-supervised short text classification, leveraging full advantage of limited labeled data and large unlabeled data through information propagation

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15

Sarunya, Kanjanawattana, and Kimura Masaomi. "BRAIN Journal - ANNSVM: A Novel Method for Graph-Type Classification by Utilization of Fourier Transformation, Wavelet Transformation, and Hough Transformation." BRAIN: Broad Research in Artificial Intelligence and Neuroscience 8, no. 2 (2017): 5–25. https://doi.org/10.5281/zenodo.1045375.

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ABSTRACT Image classification plays a vital role in many areas of study, such as data mining and image processing; however, serious problems collectively referred to as the course of dimensionality have been encountered in previous studies as factors that reduce system performance. Furthermore, we also confront the problem of different graph characteristics even if graphs belong to same types. In this study, we propose a novel method of graph-type classification. Using our approach, we open up a new solution of high-dimensional images and address problems of different characteristics by conver

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16

Gopalakrishnan, Atul Anand, Jakir Hossain, Tuğrulcan Elmas, and Ahmet Erdem Sariyüce. "Large Engagement Networks for Classifying Coordinated Campaigns and Organic Twitter Trends." Proceedings of the International AAAI Conference on Web and Social Media 19 (June 7, 2025): 688–702. https://doi.org/10.1609/icwsm.v19i1.35839.

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Social media users and inauthentic accounts, such as bots, may coordinate in promoting their topics. Such topics may give the impression that they are organically popular among the public, even though they are astroturfing campaigns that are centrally managed. It is challenging to predict if a topic is organic or a coordinated campaign due to the lack of reliable ground truth. In this paper, we create such a ground truth by detecting the campaigns promoted by ephemeral astroturfing attacks. These attacks push any topic to Twitter’s (X) trends list by employing bots that tweet in a coordinated

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17

Zhou, Yong Zheng, Ru Dong Ouyang, Han Jun Wu, and De Juan Kong. "Research of Ceramic Raw Materials Classification Base on Multivariate Chart Method." Applied Mechanics and Materials 246-247 (December 2012): 1066–70. http://dx.doi.org/10.4028/www.scientific.net/amm.246-247.1066.

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In this paper, it was discussed the Rader chart, trigonometric polynomial graph and the constellation graph which can be programmed and realized by MATLAB SOFEWARE and got it applied in the research of Ceramic Raw Materials classification used the replacing theory of same type kaolin to reduce the cost of raw materials and reduce the cost of transport. To improve the economic benefits of the production of ceramic enterprises, and the research results will be widely applied in industrial production for the purpose of guiding ceramic.

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18

Dobesova, Zdena. "AUTOMATIC DATA CLASSIFICATION BASED ON THE TRIANGULAR GRAPH FOR THEMATIC MAPS." Geodesy and Cartography 41, no. 1 (2015): 1–8. http://dx.doi.org/10.3846/20296991.2015.1024457.

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A triangular point graph helps in the process of data classification for a thematic map. A triangular graph can be used for a situation that is described by three variables. The total sum of variables is 100%. The proportion of three variables is plotted in an equilateral triangular graph where each side represents a coordinate for one variable. A triangular graph displays the proportions of the three variables. The position of the point indicates the type (class) of the situation in the triangular graph. The typology of the situation can be subsequently expressed in the map. We have created a

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19

Cho, Ilwoo, and Palle Jorgensen. "An Index for Graphs and Graph Groupoids." Axioms 11, no. 2 (2022): 47. http://dx.doi.org/10.3390/axioms11020047.

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In this paper, we consider certain quantities that arise in the images of the so-called graph-tree indexes of graph groupoids. In text, the graph groupoids are induced by connected finite-directed graphs with more than one vertex. If a graph groupoid GG contains at least one loop-reduced finite path, then the order of G is infinity; hence, the canonical groupoid index G:K of the inclusion K⊆G is either ∞ or 1 (under the definition and a natural axiomatization) for the graph groupoids K of all “parts” K of G. A loop-reduced finite path generates a semicircular element in graph groupoid algebra.

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20

Zhao, Wentao, Dalin Zhou, Xinguo Qiu, and Wei Jiang. "How to Represent Paintings: A Painting Classification Using Artistic Comments." Sensors 21, no. 6 (2021): 1940. http://dx.doi.org/10.3390/s21061940.

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The goal of large-scale automatic paintings analysis is to classify and retrieve images using machine learning techniques. The traditional methods use computer vision techniques on paintings to enable computers to represent the art content. In this work, we propose using a graph convolutional network and artistic comments rather than the painting color to classify type, school, timeframe and author of the paintings by implementing natural language processing (NLP) techniques. First, we build a single artistic comment graph based on co-occurrence relations and document word relations and then t

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21

R. Pappathi, M. P. Syed Ali Nisaya. "l-HILBERT MEAN LABELING OF SOME PATH RELATED GRAPHS." Tuijin Jishu/Journal of Propulsion Technology 44, no. 3 (2023): 4710–16. http://dx.doi.org/10.52783/tjjpt.v44.i3.2637.

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Let be a graph with vertices and edges. The th hilbert number is denoted by and is defined by where A - hilbert mean labeling is an injective function , where that induces a bijection defined by for all . A graph which admits such labeling is called a - hilbert mean graph. In this paper, a new type of labeling called - hilbert mean labeling is introduced and the path related graphs is studied. AMS Subject Classification – 05C78

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22

Peng, Feifei, Wei Lu, Wenxia Tan, Kunlun Qi, Xiaokang Zhang, and Quansheng Zhu. "Multi-Output Network Combining GNN and CNN for Remote Sensing Scene Classification." Remote Sensing 14, no. 6 (2022): 1478. http://dx.doi.org/10.3390/rs14061478.

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Scene classification is an active research area in the remote sensing (RS) domain. Some categories of RS scenes, such as medium residential and dense residential scenes, would contain the same type of geographical objects but have various spatial distributions among these objects. The adjacency and disjointness relationships among geographical objects are normally neglected by existing RS scene classification methods using convolutional neural networks (CNNs). In this study, a multi-output network (MopNet) combining a graph neural network (GNN) and a CNN is proposed for RS scene classification

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23

Ren, Kai, and Khaliun Buyandelger. "Construction of a Type Knowledge Graph Based on the Value Cognitive Turn of Characteristic Villages: An Application in Jixi, Anhui Province, China." Land 13, no. 1 (2023): 9. http://dx.doi.org/10.3390/land13010009.

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Currently, Chinese villages are grappling with the issue of regional value collapse within the long-standing ‘urban-rural dual system’ strategy. Characteristic villages, as integral components of the urban–rural hierarchical spatial system and pivotal agents in rural development, wield significant influence in addressing China’s rural crises. The construction practice of characteristic villages showcases the cognitive evolution of ‘element-industry-function-type’. Within the value perception of characteristic villages, these practices reflect fundamental orientations in the interaction between

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24

Melo, Andre, Johanna Völker, and Heiko Paulheim. "Type Prediction in Noisy RDF Knowledge Bases Using Hierarchical Multilabel Classification with Graph and Latent Features." International Journal on Artificial Intelligence Tools 26, no. 02 (2017): 1760011. http://dx.doi.org/10.1142/s0218213017600119.

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Semantic Web knowledge bases, in particular large cross-domain data, are often noisy, incorrect, and incomplete with respect to type information. This incompleteness can be reduced, as previous work shows, with automatic type prediction methods. Most knowledge bases contain an ontology defining a type hierarchy, and, in general, entities are allowed to have multiple types (classes of an instance assigned with the rdf:type relation). In this paper, we exploit these characteristics and formulate the type prediction problem as hierarchical multi classification, where the labels are types. We eval

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25

Liu, Ziyu, and Yacheng Song. "Unsupervised Plot Morphology Classification via Graph Attention Networks: Evidence from Nanjing’s Walled City." Land 14, no. 7 (2025): 1469. https://doi.org/10.3390/land14071469.

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Urban plots are pivotal links between individual buildings and the city fabric, yet conventional plot classification methods often overlook how buildings interact within each plot. This oversight is particularly problematic in the irregular fabrics typical of many Global South cities. This study aims to create a plot classification method that jointly captures metric and configurational characteristics. Our approach converts each cadastral plot into a graph whose nodes are building centroids and whose edges reflect Delaunay-based proximity. The model then learns unsupervised graph embeddings w

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26

WILLIAMS, GERALD. "GROUPS OF FIBONACCI TYPE REVISITED." International Journal of Algebra and Computation 22, no. 08 (2012): 1240002. http://dx.doi.org/10.1142/s0218196712400024.

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This article concerns a class of groups of Fibonacci type introduced by Johnson and Mawdesley that includes Conway's Fibonacci groups, the Sieradski groups, and the Gilbert–Howie groups. This class of groups provides an interesting focus for developing the theory of cyclically presented groups and, following questions by Bardakov and Vesnin and by Cavicchioli, Hegenbarth, and Repovš, they have enjoyed renewed interest in recent years. We survey results concerning their algebraic properties, such as isomorphisms within the class, the classification of the finite groups, small cancellation prope

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27

Mallik, Saurav, and Zhongming Zhao. "Graph- and rule-based learning algorithms: a comprehensive review of their applications for cancer type classification and prognosis using genomic data." Briefings in Bioinformatics 21, no. 2 (2019): 368–94. http://dx.doi.org/10.1093/bib/bby120.

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AbstractCancer is well recognized as a complex disease with dysregulated molecular networks or modules. Graph- and rule-based analytics have been applied extensively for cancer classification as well as prognosis using large genomic and other data over the past decade. This article provides a comprehensive review of various graph- and rule-based machine learning algorithms that have been applied to numerous genomics data to determine the cancer-specific gene modules, identify gene signature-based classifiers and carry out other related objectives of potential therapeutic value. This review foc

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28

G, Jayagopi, and Pushpa S. "Arrhythmia Classification Based on Combined Chaotic and Statistical Feature Extraction." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 1 (2018): 127. http://dx.doi.org/10.11591/ijeecs.v12.i1.pp127-136.

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Obvious information content in Electro cardio graph has become mandatory to reveal the abnormalities in the heart functions. Arrhythmia is commonly seen heart disorder and results in fatal end, if not identified and treated properly within time limits. The straight forward scene in such diagnosis is to detect the salient features from the Electro cardio graph data using signal processing methods followed by proper classification methods. 16 classes of Arrhythmia had been classified in this work by adopting the traditional method of abnormality detection while introducing a novelty in the type

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29

G., Jayagopi, and Pushpa S. "Arrhythmia Classification Based on Combined Chaotic and Statistical Feature Extraction." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 1 (2018): 127–36. https://doi.org/10.11591/ijeecs.v12.i1.pp127-136.

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Анотація:

Obvious information content in Electro cardio graph has become mandatory to reveal the abnormalities in the heart functions. Arrhythmia is commonly seen heart disorder and results in fatal end, if not identified and treated properly within time limits. The straight forward scene in such diagnosis is to detect the salient features from the Electro cardio graph data using signal processing methods followed by proper classification methods. 16 classes of Arrhythmia had been classified in this work by adopting the traditional method of abnormality detection while introducing a novelty in the type

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30

Romanov, Vitaly Anatolyevich, and Vladimir Vladimirovich Ivanov. "Comparison of Graph Embeddings for Source Code with Text Models Based on CNN and CodeBERT Architectures." Proceedings of the Institute for System Programming of the RAS 35, no. 1 (2023): 237–64. http://dx.doi.org/10.15514/ispras-2023-35(1)-15.

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One possible way to reduce bugs in source code is to create intelligent tools that make the development process easier. Such tools often use vector representations of the source code and machine learning techniques borrowed from the field of natural language processing. However, such approaches do not take into account the specifics of the source code and its structure. This work studies methods for pretraining graph vector representations for source code, where the graph represents the structure of the program. The results show that graph embeddings allow to achieve an accuracy of classifying

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31

Zhang, Min, Guohua Geng, Sheng Zeng, and Huaping Jia. "Knowledge Graph Completion for the Chinese Text of Cultural Relics Based on Bidirectional Encoder Representations from Transformers with Entity-Type Information." Entropy 22, no. 10 (2020): 1168. http://dx.doi.org/10.3390/e22101168.

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Knowledge graph completion can make knowledge graphs more complete, which is a meaningful research topic. However, the existing methods do not make full use of entity semantic information. Another challenge is that a deep model requires large-scale manually labelled data, which greatly increases manual labour. In order to alleviate the scarcity of labelled data in the field of cultural relics and capture the rich semantic information of entities, this paper proposes a model based on the Bidirectional Encoder Representations from Transformers (BERT) with entity-type information for the knowledg

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32

Huang, Danyi, Zhuang Bian, Qinli Qiu, Yinmao Wang, Dongmei Fan, and Xiaochang Wang. "Identification of Similar Chinese Congou Black Teas Using an Electronic Tongue Combined with Pattern Recognition." Molecules 24, no. 24 (2019): 4549. http://dx.doi.org/10.3390/molecules24244549.

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It is very difficult for humans to distinguish between two kinds of black tea obtained with similar processing technology. In this paper, an electronic tongue was used to discriminate samples of seven different grades of two types of Chinese Congou black tea. The type of black tea was identified by principal component analysis and discriminant analysis. The latter showed better results. The samples of the two types of black tea distributed on the two sides of the region graph were obtained from discriminant analysis, according to tea type. For grade discrimination, we determined grade predicti

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33

POPA, SORIN. "CLASSIFICATION OF ACTIONS OF DISCRETE AMENABLE GROUPS ON AMENABLE SUBFACTORS OF TYPE II." International Journal of Mathematics 21, no. 12 (2010): 1663–95. http://dx.doi.org/10.1142/s0129167x10006343.

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We prove a classification result for properly outer actions σ of discrete amenable groups G on strongly amenable subfactors of type II, N ⊂ M, a class of subfactors that were shown to be completely classified by their standard invariant [Formula: see text], in [27]. The result shows that the action σ is completely classified in terms of the action it induces on [Formula: see text]. As an application of this, we obtain that inclusions of type III λ factors, 0 < λ < 1, having discrete decomposition and strongly amenable graph, are completely classified by their standard invariant.

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34

Маторин, С. И., С. В. Гуль, and Н. В. Щербинина. "THREE-DIMENSIONAL SYSTEM-OBJECT CLASSIFICATION FOR PREDICTION AND CONTROL SUPPORT." Научно-техническая информация. Серия 2: Информационные процессы и системы, no. 12 (December 1, 2023): 1–13. http://dx.doi.org/10.36535/0548-0027-2023-12-1.

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Анотація:

Рассматриваются недостатки современных способов классифицирования объектов и процессов. Предлагается способ построения трехмерных классификаций, позволяющий устранить некоторые из этих недостатков, основанный на системно-объектном подходе, использующем идеи многомерного классифицирования и естественной классификации. В качестве плоскостей классифицирования используются три основные системные характеристики: структурная (узел), функциональная (функция) и субстанциальная (объект), что позволяет осуществлять классифицирование по видам функционального запроса к системе со стороны системы более выс

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Fionda, Valeria, and Giuseppe Pirrò. "Learning Triple Embeddings from Knowledge Graphs." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 3874–81. http://dx.doi.org/10.1609/aaai.v34i04.5800.

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Анотація:

Graph embedding techniques allow to learn high-quality feature vectors from graph structures and are useful in a variety of tasks, from node classification to clustering. Existing approaches have only focused on learning feature vectors for the nodes and predicates in a knowledge graph. To the best of our knowledge, none of them has tackled the problem of directly learning triple embeddings. The approaches that are closer to this task have focused on homogeneous graphs involving only one type of edge and obtain edge embeddings by applying some operation (e.g., average) on the embeddings of the

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Peng, Rongrong, Changfen Gong, and Shuai Zhao. "Multi-Sensor Information Fusion with Multi-Scale Adaptive Graph Convolutional Networks for Abnormal Vibration Diagnosis of Rolling Mill." Machines 13, no. 1 (2025): 30. https://doi.org/10.3390/machines13010030.

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Анотація:

Graph data and multi-sensor information fusion have been integrated into the abnormal vibration type classification and the identification of the rolling mill for extracting spatial–temporal and robust features. However, most of the existing deep learning (DL) based methods exploit only single sensor information and Euclidean space data, which results in incomplete information contained in the features extracted by in-depth networks. To solve this issue, a multi-sensor information fusion with multi-scale adaptive graph convolutional networks (M2AGCNs) framework is proposed to model graph data

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37

Yuzana, Win, and Masada Tomonari. "Bidirectional Extraction of Phrases for Expanding Queries in Academic Paper Retrieval." International Journal of Advanced Research in Artificial Intelligence (IJARAI) Volume 5, Issue 1 (2016): 27–33. https://doi.org/10.14569/IJARAI.2016.050105.

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Анотація:

This paper proposes a new method for query expansion based on bidirectional extraction of phrases as word n-grams from research paper titles. The proposed method aims to extract information relevant to users’ needs and interests and thus to provide a useful system for technical paper retrieval. The outcome of proposed method are the trigrams as phrases that can be used for query expansion. <em>First</em>, word trigrams are extracted from research paper titles. <em>Second</em>, a co-occurrence graph of the extracted trigrams is constructed. To construct the co-occurrence graph, the direct

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Wang, Yan, Xiao Feng Ma, and Miao Zhu. "A knowledge graph algorithm enabled deep recommendation system." PeerJ Computer Science 10 (July 30, 2024): e2010. http://dx.doi.org/10.7717/peerj-cs.2010.

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Анотація:

Personalized learning resource recommendations may help resolve the difficulties of online education that include learning mazes and information overload. However, existing personalized learning resource recommendation algorithms have shortcomings such as low accuracy and low efficiency. This study proposes a deep recommendation system algorithm based on a knowledge graph (D-KGR) that includes four data processing units. These units are the recommendation unit (RS unit), the knowledge graph feature representation unit (KGE unit), the cross compression unit (CC unit), and the feature extraction

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Meng, Xiangzhen, Bo Jing, Shenglong Wang, Jinxin Pan, Yifeng Huang, and Xiaoxuan Jiao. "Fault Knowledge Graph Construction and Platform Development for Aircraft PHM." Sensors 24, no. 1 (2023): 231. http://dx.doi.org/10.3390/s24010231.

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Анотація:

To tackle the problems of over-reliance on traditional experience, poor troubleshooting robustness, and slow response by maintenance personnel to changes in faults in the current aircraft health management field, this paper proposes the use of a knowledge graph. The knowledge graph represents troubleshooting in a new way. The aim of the knowledge graph is to improve the correlation between fault data by representing experience. The data source for this study consists of the flight control system manual and typical fault cases of a specific aircraft type. A knowledge graph construction approach

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40

Ma, Xuesong, and Ruji Wang. "Trivalent Non-symmetric Vertex-Transitive Graphs of Order at Most 150." Algebra Colloquium 15, no. 03 (2008): 379–90. http://dx.doi.org/10.1142/s1005386708000370.

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Анотація:

Let X be a simple undirected connected trivalent graph. Then X is said to be a trivalent non-symmetric graph of type (II) if its automorphism group A = Aut (X) acts transitively on the vertices and the vertex-stabilizer Av of any vertex v has two orbits on the neighborhood of v. In this paper, such graphs of order at most 150 with the basic cycles of prime length are investigated, and a classification is given for such graphs which are non-Cayley graphs, whose block graphs induced by the basic cycles are non-bipartite graphs.

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41

Zhong, Zhicheng, Jixiang Wan, Hao Bu, et al. "Individual Importance Classification of Urban Stormwater Channel Networks: A Novel Approach Based on Permutation and Algebraic Graph Theory." Water 16, no. 22 (2024): 3242. http://dx.doi.org/10.3390/w16223242.

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Анотація:

The frequency and intensity of urban flooding continuously increase due to the dual influences of climate change and urbanization. Conducting individual importance classification of urban stormwater channel networks (USCNs) is of significant importance for alleviating urban flooding and facilitating targeted stormwater management implementation. However, a quantitative classification method is lacking for trellis networks, which are a common type of USCN. This study proposed a novel importance classification methodology for channel segments in most types of USCNs, especially suitable for trell

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42

Maheswara Rao, Saka Uma, Keshetti Sreekala, Pulluri Srinivas Rao, Nalla Shirisha, Gunnam Srinivas, and Erry Sreedevi. "Plant disease classification using novel integration of deep learning CNN and graph convolutional networks." Indonesian Journal of Electrical Engineering and Computer Science 36, no. 3 (2024): 1721. http://dx.doi.org/10.11591/ijeecs.v36.i3.pp1721-1730.

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Plant diseases present substantial challenges to global agriculture, significantly affecting crop yields and jeopardizing food security. Accurate and timely detection of these diseases is paramount for mitigating their adverse effects. This paper proposes a novel approach for plant disease classification by integrating convolutional neural networks (CNNs) and graph convolutional networks (GCNs). The model aims to enhance classification accuracy by leveraging both visual features extracted by CNNs and relational information captured by GCNs. Using a Kaggle dataset containing images of diseased

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Saka, Uma Maheswara Rao Keshetti Sreekala Pulluri Srinivas Rao Nalla Shirisha Gunnam Srinivas Erry Sreedevi. "Plant disease classification using novel integration of deep learning CNN and graph convolutional networks." Indonesian Journal of Electrical Engineering and Computer Science 36, no. 3 (2024): 1721–30. https://doi.org/10.11591/ijeecs.v36.i3.pp1721-1730.

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Анотація:

Plant diseases present substantial challenges to global agriculture, significantly affecting crop yields and jeopardizing food security. Accurate and timely detection of these diseases is paramount for mitigating their adverse effects. This paper proposes a novel approach for plant disease classification by integrating convolutional neural networks (CNNs) and graph convolutional networks (GCNs). The model aims to enhance classification accuracy by leveraging both visual features extracted by CNNs and relational information captured by GCNs. Using a Kaggle dataset containing images of diseased

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44

Radha, K., and S. Sri Harini. "Characterizations of the Direct Sum of Two Difference - Mean Fuzzy Graphs." Indian Journal Of Science And Technology 17, no. 20 (2024): 2043–49. http://dx.doi.org/10.17485/ijst/v17i20.1017.

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Objectives: This study presents a new type of fuzzy graph known as the difference mean fuzzy graph by introducing difference mean edge. Methodology: In this paper, difference mean edge in a fuzzy graph is defined by considering the relationship between the membership value of the edge and the membership values of its end vertices. Also, difference mean fuzzy graph is defined and its properties are derived. Findings: The difference mean edge and the difference mean fuzzy graph are introduced. The requirements for an edge in the direct sum of two fuzzy graphs to be a difference mean edge are fou

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45

LIU, MINGXIA, and DAOQIANG ZHANG. "SPARSITY SCORE: A NOVEL GRAPH-PRESERVING FEATURE SELECTION METHOD." International Journal of Pattern Recognition and Artificial Intelligence 28, no. 04 (2014): 1450009. http://dx.doi.org/10.1142/s0218001414500098.

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As thousands of features are available in many pattern recognition and machine learning applications, feature selection remains an important task to find the most compact representation of the original data. In the literature, although a number of feature selection methods have been developed, most of them focus on optimizing specific objective functions. In this paper, we first propose a general graph-preserving feature selection framework where graphs to be preserved vary in specific definitions, and show that a number of existing filter-type feature selection algorithms can be unified withi

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46

Wu, Yang-Han, Yu-An Huang, Jian-Qiang Li, et al. "Knowledge graph embedding for profiling the interaction between transcription factors and their target genes." PLOS Computational Biology 19, no. 6 (2023): e1011207. http://dx.doi.org/10.1371/journal.pcbi.1011207.

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Interactions between transcription factor and target gene form the main part of gene regulation network in human, which are still complicating factors in biological research. Specifically, for nearly half of those interactions recorded in established database, their interaction types are yet to be confirmed. Although several computational methods exist to predict gene interactions and their type, there is still no method available to predict them solely based on topology information. To this end, we proposed here a graph-based prediction model called KGE-TGI and trained in a multi-task learnin

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47

K, Radha, and Sri Harini S. "Characterizations of the Direct Sum of Two Difference - Mean Fuzzy Graphs." Indian Journal of Science and Technology 17, no. 20 (2024): 2043–49. https://doi.org/10.17485/IJST/v17i20.1017.

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Анотація:

Abstract <strong>Objectives:</strong> This study presents a new type of fuzzy graph known as the difference mean fuzzy graph by introducing difference mean edge.<strong> Methodology:</strong> In this paper, difference mean edge in a fuzzy graph is defined by considering the relationship between the membership value of the edge and the membership values of its end vertices. Also, difference mean fuzzy graph is defined and its properties are derived.<strong> Findings:</strong> The difference mean edge and the difference mean fuzzy graph are introduced. The requirements f

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48

Wang, Ruiheng, Hongliang Zhu, Lu Wang, Zhaoyun Chen, Mingcheng Gao, and Yang Xin. "User Identity Linkage Across Social Networks by Heterogeneous Graph Attention Network Modeling." Applied Sciences 10, no. 16 (2020): 5478. http://dx.doi.org/10.3390/app10165478.

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Анотація:

Today, social networks are becoming increasingly popular and indispensable, where users usually have multiple accounts. It is of considerable significance to conduct user identity linkage across social networks. We can comprehensively depict diversified characteristics of user behaviors, accurately model user profiles, conduct recommendations across social networks, and track cross social network user behaviors by user identity linkage. Existing works mainly focus on a specific type of user profile, user-generated content, and structural information. They have problems of weak data expression

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Nam, Tran Le. "Classification of j-maximal spacelike affine translation surfaces in the Minkovski space i31 with density." Tạp chí Khoa học 15, no. 3 (2019): 36. http://dx.doi.org/10.54607/hcmue.js.15.3.140(2018).

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Анотація:

An affine translation surface is a graph of a function introduced by Liu and Yu in 2013. The article considers the spacelike affine translation surfaces in the Minkowski space with density establishing the Lagrange’s equation type for -maximal surface, classifying -maximal spacelike affine translation surfaces. The result obtains two parameters and . From that, the Calabi – Bernstein theorem in this space is not true because two function and are defined on

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Babkov, Yu V., E. E. Belova, and M. I. Potapov. "On the classification of motive power failures." Dependability 21, no. 4 (2021): 12–19. http://dx.doi.org/10.21683/1729-2646-2021-21-4-12-19.

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The Aim of the article is to develop a motive power failure classification to enable substantiated definition of dependability requirements for motive power as a part of a railway transportation system, as well as for organizing systematic measures to ensure a required level of its dependability over the life cycle. Methods. The terminology of interstate dependability-related standards was analysed and the two classifications used by OJSC “RZD” for estimating the dependability of technical systems and motive power were compared. The dependability of railway transportation systems is studied us

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