VF3-Light: A lightweight subgraph isomorphism algorithm and its experimental evaluation

Carletti, Vincenzo; Foggia, Pasquale; Greco, Antonio; Vento, Mario; Vigilante, Vincenzo

doi:10.1016/j.patrec.2019.07.001

Cited by 20 publications

(10 citation statements)

References 8 publications

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“…In the formula, M represents the number of recommended categories, E ij represents the possibility that resource i enters the recommendation list j, and x ij represents the possibility that resource i does not belong to the recommendation list j. The subgraph algorithm [23] is used to describe the weight of resource distribution in the entire space [24], which can be expressed by…”

Section: Ideological and Political Course Networkmentioning

confidence: 99%

Design of Network-Assisted Teaching of Ideological and Political Courses for College Students Based on Android System

Sun

2022

Wireless Communications and Mobile Computing

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In order to be able to provide learning resources for learners anytime and anywhere and improve the quality of online teaching, a network-assisted teaching system for college students’ ideological and political courses based on the Android system is designed. The characteristics of the Android system platform and its hierarchical structure are analyzed, and the overall structure of the network-assisted teaching system was designed based on it and through the construction of the system user login module, learning resources module, operation management module, unit test module, and teaching interface display module, so as to achieve the effect of network assisted ideological and political course teaching. The preferences of students were fully considered, the needs of students with different resource spaces were matched, and the genetic algorithm is used to share the information of network teaching resources to meet the needs of ideological and political teaching. According to the experimental results, the system designed in this paper has high accuracy in the recommended content of ideological and political education resources and the coverage of resource recommendation is relatively high, indicating that the application effect of the system is better.

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Section: Ideological and Political Course Networkmentioning

confidence: 99%

Design of Network-Assisted Teaching of Ideological and Political Courses for College Students Based on Android System

Sun

2022

Wireless Communications and Mobile Computing

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“…It is worth noting that our proposed method still achieves an F1-score of 0.98 on the IMDB-BINARY whose graphs do not have node features, showing that our model can predict matching relationships based on structural information only. From Table 4 , We found that the running time of AEDNet is faster than the exact algorithm VF3 [9] on larger graphs and VF3 is efficient on small graphs. The results show that despite being executed by python, our proposed end-to-end learning-based method is much more efficient on larger graphs.…”

Section: Effectiveness and Efficiencymentioning

confidence: 97%

“…Subgraph isomorphism is a generalization of the graph isomorphism problem. Compared with the graph matching problem, the subgraph matching problem is generally more challenging, mainly due to the different sizes between the two graphs, resulting in the considerable large space of solutions [9,10] . Subgraph isomorphism can be divided into induced and non-induced subgraph isomorphism problems [11] .…”

Section: Introductionmentioning

confidence: 99%

AEDNet: Adaptive Edge-Deleting Network For Subgraph Matching

Lan

et al. 2023

Pattern Recognition

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“…VF3 [10] also improves VF2 by proposing heuristics for reducing the search space size and the time of processing each state. Moreover, VF3-Light [9]is another algorithm that eliminates some of VF3's heuristics which results in shorter running time.…”

Section: Structural Graph Pattern Matchingmentioning

confidence: 99%

A Survey on Distributed Graph Pattern Matching in Massive Graphs

et al. 2021

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Besides its NP-completeness, the strict constraints of subgraph isomorphism are making it impractical for graph pattern matching (GPM) in the context of big data. As a result, relaxed GPM models have emerged as they yield interesting results in a polynomial time. However, massive graphs generated by mostly social networks require a distributed storing and processing of the data over multiple machines, thus, requiring GPM to be revised by adopting new paradigms of big graphs processing, e.g., Think-Like-A-Vertex and its derivatives. This article discusses and proposes a classification of distributed GPM approaches with a narrow focus on the relaxed models.

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VF3-Light: A lightweight subgraph isomorphism algorithm and its experimental evaluation

Cited by 20 publications

References 8 publications

Design of Network-Assisted Teaching of Ideological and Political Courses for College Students Based on Android System

Design of Network-Assisted Teaching of Ideological and Political Courses for College Students Based on Android System

AEDNet: Adaptive Edge-Deleting Network For Subgraph Matching

A Survey on Distributed Graph Pattern Matching in Massive Graphs

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