Understanding Graph Databases: A Comprehensive Tutorial and Survey | Paper Citation Record

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This paper cites Towards enhancing the robustness of scale-free iot networks by an intelligent rewiring mechanism.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Towards enhancing the robustness of scale-free iot networks by an intelligent rewiring mechanism

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Iot based recent trends in engineering and its applications

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Catalytic and binding sites prediction in globular proteins through discrete markov chains and network centrality measures

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Distance measures for embedded graphs

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Ganie, and Yilun Shang

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Understanding Graph Databases: A Comprehensive Tutorial and Survey On identifying the critical nodes and vulnerable edges for increasing network security

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Reciprocal degree distance and graph properties

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Mapping rdf databases to property graph databases

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Unresolved cited work

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Empirical evaluation of a cloud-based graph database: the case of neptune

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Species environmental niche distribution modeling for panthera tigris tigris ‘royal bengal tiger’using machine learning

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Assessing the computational limits of graphdbs’ engines-a comparison study between neo4j and apache spark

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Term-graph anti-unification

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Analysis of native multi-model database using arangodb

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This paper cites Data fusion and graph analysis in fraud transaction detection: walkthrough of a case study.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Data fusion and graph analysis in fraud transaction detection: walkthrough of a case study

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This paper cites Demystifying graph databases: Analysis and taxonomy of data organization, system designs, and graph queries.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Demystifying graph databases: Analysis and taxonomy of data organization, system designs, and graph queries

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Deep learning with graph convolutional networks: An overview and latest applications in computational intelligence

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Hybrid par- allel implementation of multiple sequence alignment software clustalw on intel xeon phi

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Understanding Graph Databases: A Comprehensive Tutorial and Survey The influence of color, color as influence: structuring tools for the design of a graphic design project

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Algorithm for solving multicriteria problem of appointments on the networks

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Inductive link prediction banking fraud detection system using homogeneous graph-based ma- chine learning model

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Understanding Graph Databases: A Comprehensive Tutorial and Survey A comprehensive survey of graph embedding: Problems, techniques, and applications

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Combinatorial optimization and reasoning with graph neural networks

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This paper cites Efficiency comparison of pathfinding algorithms a* and dijkstra’s in two dimensional grid.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Efficiency comparison of pathfinding algorithms a* and dijkstra’s in two dimensional grid

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Multi-view attribute graph convolution networks for clustering

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Graphrc: Accelerating graph processing on dual-addressing memory with vertex merging

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This paper cites Applications of link prediction in social networks: A review.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Applications of link prediction in social networks: A review

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Temporal pattern recognition in graph data structures

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Efficient vector influence clustering coefficient based directed community detection method

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Review paper oncom- plexity reduction in relational database using neo4j graph database

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Query-based performance comparison of graph database and relational database

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Thanou, M

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Understanding Graph Databases: A Comprehensive Tutorial and Survey On the rank of the distance matrix of graphs

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Understanding Graph Databases: A Comprehensive Tutorial and Survey On Node Features for Graph Neural Networks

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Understanding Graph Databases: A Comprehensive Tutorial and Survey A methodological eval- uation of natural user interfaces for immersive 3d graph explorations

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Reactome graph database: Efficient access to complex pathway data

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Graph theory in paediatric epilepsy: a systematic review

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Graphscope: a unified engine for big graph processing

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Detection of influential nodes using social networks analysis based on network metrics

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Graph neural networks for recommender system

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Understanding Graph Databases: A Comprehensive Tutorial and Survey GraphNAS: Graph Neural Architecture Search with Reinforcement Learning

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Incre- mental strong connectivity and 2-connectivity in directed graphs

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Graph Similarity Based on Matrix Norms

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Neural message passing for quantum chemistry

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Understanding Graph Databases: A Comprehensive Tutorial and Survey b embedding vertex intrinsic relevance in network analysis: the case of betweenness

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Challenges with graph interpretation: A review of the literature

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Overlapping community detection using multi-objective approach and rough clustering

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Improving graph neural network for session-based recommendation system via non-sequential interactions

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Enterprise Analytics using Graph Database and Graph-based Deep Learning

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Collabora- tive filtering via graph signal processing

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Understanding Graph Databases: A Comprehensive Tutorial and Survey A multi- level clustering technique for community detection

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Understanding Graph Databases: A Comprehensive Tutorial and Survey A graph theory-based modeling of functional brain connectivity based on eeg: a systematic review in the context of neuroergonomics

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Web tool for graph embeddings representation techniques evaluation

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Learning graph databases: Neo4j an overview

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Building graphs with maximum connectivity

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Graph neural network for traffic forecasting: A survey

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Scalable and optimal planning based on pregel

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Application of deep learning methods in biological networks

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Kgnn: Harnessing kernel-based networks for semi- supervised graph classification

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Declarative and distributed graph analytics with gradoop

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Near-storage accelerator for bulk graph ingestion

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Understanding Graph Databases: A Comprehensive Tutorial and Survey A circular layout algorithm for attributed hierarchical graphs with ports

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Understanding Graph Databases: A Comprehensive Tutorial and Survey Graffinity: Visualizing connectivity in large graphs

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Unavailable: canonical work link unavailable.

Observation 52ad535d-9cab-47cd-a6a3-bd2da74e78ec · outbound

This paper cites A shortest path graph attention network and non-traditional multi- deep layouts in robotic mobile fulfillment system.

Understanding Graph Databases: A Comprehensive Tutorial and Survey A shortest path graph attention network and non-traditional multi- deep layouts in robotic mobile fulfillment system

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Resolution: unresolved; no resolver link, observed 2026-08-12T20:07:22.738686Z

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Observation 75004e1c-cf6a-40b1-902b-48e70fc3775b · outbound

This paper cites What is a complex graph? Physica A: Statistical Mechanics and its Applications , 387(11):2637– 2652, 2008.

Understanding Graph Databases: A Comprehensive Tutorial and Survey What is a complex graph? Physica A: Statistical Mechanics and its Applications , 387(11):2637– 2652, 2008

Reference 65

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Observation d9d5ee9e-5801-4590-8bdc-7396fea72ae7 · outbound

This paper cites Graph rewriting techniques in engineering design.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Graph rewriting techniques in engineering design

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T20:07:22.756082Z

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Observation cd09b6c6-57fe-4604-8d9c-5bfdc3384f57 · outbound

This paper cites An efficient graph visualisation framework for refactorerl.

Understanding Graph Databases: A Comprehensive Tutorial and Survey An efficient graph visualisation framework for refactorerl

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-12T20:07:22.765928Z

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Observation 89189087-766b-4257-958d-d6178d039ce5 · outbound

This paper cites Data-to-question generation using deep learning.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Data-to-question generation using deep learning

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-12T20:07:22.777496Z

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Observation da9636c5-0c60-40f9-9abb-be0ddc2302fb · outbound

This paper cites A guide to conquer the biological network era using graph theory.

Understanding Graph Databases: A Comprehensive Tutorial and Survey A guide to conquer the biological network era using graph theory

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.602974Z

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Observation d89d5d6a-0176-43bc-a603-2c46fdafbdab · outbound

This paper cites Efficient edge rewiring strategies for enhancement in network capacity.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Efficient edge rewiring strategies for enhancement in network capacity

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.575150Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cdb9501e-e7c8-4e77-916e-16e82551d21d · outbound

This paper cites Conte, Hiroki Arimura, and T.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Conte, Hiroki Arimura, and T

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.552934Z

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Observation 2375405d-c305-4a3a-9f2a-841c52bdccc6 · outbound

This paper cites Efficiency analysis of con- ventional and weighted grid-based pathfinding algorithms: A perfor- mance comparative study.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Efficiency analysis of con- ventional and weighted grid-based pathfinding algorithms: A perfor- mance comparative study

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.517783Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c05c90de-f311-4d09-9c7d-c31344a520a2 · outbound

This paper cites Measuring and improving the core resilience of networks.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Measuring and improving the core resilience of networks

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.494394Z

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Observation 323f18ce-26bf-47e6-b5c3-113735af5285 · outbound

This paper cites The maximum eigenvalue of the brain functional network adjacency matrix: Meaning and application in mental fatigue evaluation.

Understanding Graph Databases: A Comprehensive Tutorial and Survey The maximum eigenvalue of the brain functional network adjacency matrix: Meaning and application in mental fatigue evaluation

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.467543Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 45a60646-fa1b-42e7-8e37-3c89114618e4 · outbound

This paper cites Fraud detection based on graph neural networks with self-attention.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Fraud detection based on graph neural networks with self-attention

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.446279Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c6ab9bef-e555-4cee-b1ac-04cc24459f0a · outbound

This paper cites Re- alizing memory-optimized distributed graph processing.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Re- alizing memory-optimized distributed graph processing

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.415890Z

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Observation 88cf9ea8-0ceb-4db5-af63-cdb09cd10520 · outbound

This paper cites On aesthetics for user-sketched layouts of vertex-weighted graphs.

Understanding Graph Databases: A Comprehensive Tutorial and Survey On aesthetics for user-sketched layouts of vertex-weighted graphs

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.392491Z

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Observation e829ec68-d96a-4b84-ba4e-fc140879979b · outbound

This paper cites A performance optimization scheme for migrating hive data to neo4j database.

Understanding Graph Databases: A Comprehensive Tutorial and Survey A performance optimization scheme for migrating hive data to neo4j database

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.371788Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 055214e6-abcd-494b-bedc-0a05bcd45336 · outbound

This paper cites From one to all: Learning to match heterogeneous and partially overlapped graphs.

Understanding Graph Databases: A Comprehensive Tutorial and Survey From one to all: Learning to match heterogeneous and partially overlapped graphs

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.346436Z

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Observation e93ae49f-3171-4ed6-b1c5-bf3f4e852f64 · outbound

This paper cites A Survey on Graph Classification and Link Prediction based on GNN.

Understanding Graph Databases: A Comprehensive Tutorial and Survey A Survey on Graph Classification and Link Prediction based on GNN

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-12T20:07:22.883228Z

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This paper cites Graph-aware collabo- rative filtering for top-n recommendation.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Graph-aware collabo- rative filtering for top-n recommendation

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.320767Z

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Observation d84852b8-a19a-4531-9916-ea8d34bbd542 · outbound

This paper cites Emj series on statistics and methods part iv: Presenting and summarizing data using graphical tools.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Emj series on statistics and methods part iv: Presenting and summarizing data using graphical tools

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.298960Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f5ea60c7-ba94-4ba7-9118-79bd8b410d8c · outbound

This paper cites Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-12T20:07:22.916569Z

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Unavailable: canonical work link unavailable.

Observation 5b42511a-eb6a-4b4b-a13e-9365bde0fbd6 · outbound

This paper cites Stream- ing graph neural networks.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Stream- ing graph neural networks

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.272356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation eb45b506-a233-4049-b4e9-96913c445527 · outbound

This paper cites Relating aesthetics of the gui text elements with readability using font family.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Relating aesthetics of the gui text elements with readability using font family

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.247531Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 288ee372-2f3e-41ba-ba3e-6c23f2c0aa28 · outbound

This paper cites Graph theory: A comprehensive survey about graph theory applications in computer science and social networks.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Graph theory: A comprehensive survey about graph theory applications in computer science and social networks

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.218018Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f85f19cc-e8d1-4561-afac-aca49edd4f89 · outbound

This paper cites Diametral paths in total graphs of complete graphs, complete bipartite graphs and wheels.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Diametral paths in total graphs of complete graphs, complete bipartite graphs and wheels

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.190160Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9a986be3-ca95-438b-8dce-e9f34fffca42 · outbound

This paper cites A vertex-similarity clustering algorithm for community detection.

Understanding Graph Databases: A Comprehensive Tutorial and Survey A vertex-similarity clustering algorithm for community detection

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.151974Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 218c4848-83c0-4ff9-8743-117d4459aeb9 · outbound

This paper cites Lagraph: A community effort to collect graph algorithms built on top of the graphblas.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Lagraph: A community effort to collect graph algorithms built on top of the graphblas

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.110835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6a4a310c-90f6-4342-83fd-7cdc5857155b · outbound

This paper cites A comparative study of mongodb, arangodb and couchdb for big data storage.

Understanding Graph Databases: A Comprehensive Tutorial and Survey A comparative study of mongodb, arangodb and couchdb for big data storage

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.084551Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2c5c8924-c82c-45e6-ac81-de5c3b545ed5 · outbound

This paper cites Resilience analysis of new york city transportation network after snow storms.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Resilience analysis of new york city transportation network after snow storms

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.062026Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 86ef3e28-26a1-4283-9b7a-62acd9d096e6 · outbound

This paper cites Classifying the influential individuals in multi-layer social networks.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Classifying the influential individuals in multi-layer social networks

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:25.029124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7f898fac-9682-4ef7-b724-44302a5d19e6 · outbound

This paper cites Variable neighborhood search.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Variable neighborhood search

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:24.998242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9cfb4f57-1111-4d0a-8972-65186c5c0324 · outbound

This paper cites Language and hardware acceleration backend for graph processing.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Language and hardware acceleration backend for graph processing

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:24.974207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c92b13f3-05bb-42c5-9b78-2b3fd5683193 · outbound

This paper cites Financial fraud detection using graph neural networks: A systematic review.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Financial fraud detection using graph neural networks: A systematic review

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:24.945606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a88b3267-67fd-43cc-b5b4-772f3d78fb90 · outbound

This paper cites Heterogeneous in- formation fusion based graph collaborative filtering recommendation.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Heterogeneous in- formation fusion based graph collaborative filtering recommendation

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:24.920465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8d859cd5-b84f-4bad-81ea-3e2c2b718d95 · outbound

This paper cites M n– polynomials of some special graphs.

Understanding Graph Databases: A Comprehensive Tutorial and Survey M n– polynomials of some special graphs

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:24.891856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cb0cd99b-687e-4315-9e2d-e4c459b71dc8 · outbound

This paper cites Biological network analysis with deep learning.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Biological network analysis with deep learning

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-12T20:07:23.071149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb0b5ca3-2b97-405b-ba48-a103c9c5791d · outbound

This paper cites Example-based explanations for streaming fraud detection on graphs.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Example-based explanations for streaming fraud detection on graphs

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:24.834924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 16a54ba2-9348-4f5c-96ed-875493adac4a · outbound

This paper cites Network analysis with the aid of the path length matrix.

Understanding Graph Databases: A Comprehensive Tutorial and Survey Network analysis with the aid of the path length matrix

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T20:07:24.807680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Coverage vector

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