MSP: Multiple Sub-graph Query Processing using Structure-based Graph Partitioning Strategy and Map-Reduce

Shaik, Fathimabi; Subramanyam, R. B. V.; Somayajulu, Durvasula V. L. N.

doi:10.1016/j.jksuci.2016.11.007

Cited by 8 publications

(6 citation statements)

References 16 publications

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“…e key to the establishment of grid index is spatial grid division. Taking the upper left corner of martial arts teaching data spatial database as the coordinate origin [9,10], the martial arts teaching data spatial database is equally divided into M × N copies, and the obtained data objects are divided into blocks as Bl[k, j]. Among them, the division diagram of 0 ≤ k < N, 0 ≤ j < M and data grid is shown in Figure 1.…”

Section: Establishment Of Wushu Teaching Data Grid Indexmentioning

confidence: 99%

“…A priori estimation of the state vector X t+1 of each influencing factor of students' autonomous learning is made according to the existing amount of information, which is expressed by 􏽢 X t+1/t � φ t+1/t 􏽢 X t . (10) e Kalman filter gain is introduced to adjust the difference to obtain the optimal estimation [16,17]. e a priori state estimation of the error covariance matrix is expressed by…”

Section: Modeling the Relationship Between Teaching Quality And Wushu...mentioning

confidence: 99%

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Evaluation Method of Wushu Teaching Quality Based on Fuzzy Clustering

Zhu

Wang

2022

Security and Communication Networks

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The existing teaching quality evaluation methods cannot calculate the distance between the data points of teaching dataset and the center points of the large density grid, which leads to the poor classification of teaching data and the low accuracy of teaching quality evaluation. Therefore, a method of teaching quality evaluation of Wushu based on fuzzy clustering is proposed. In order to improve the comprehensiveness of teaching quality evaluation, the lost data of teaching resources were recovered. Based on this, the grid index of martial arts teaching data is established, and the relationship model between teaching quality and martial arts achievement is constructed. Based on the characteristics of Wushu teaching resources, the fuzzy clustering method is introduced to calculate the distance between each data point and the grid center with high data density. The experimental results show that the evaluation accuracy of the teaching quality is high, and the lost data can be accurately recovered. The evaluation efficiency, reliability, and stability of Wushu teaching quality are ideal.

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Section: Establishment Of Wushu Teaching Data Grid Indexmentioning

confidence: 99%

Section: Modeling the Relationship Between Teaching Quality And Wushu...mentioning

confidence: 99%

Evaluation Method of Wushu Teaching Quality Based on Fuzzy Clustering

Zhu

Wang

2022

Security and Communication Networks

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“…A new MapReduce-based multiple subgraph query processing technique is presented in [29] under distributed environment. Two works are focused in this paper such as graph partition and indexing, which is called as structure based partitioning and distributed integrated graph index.…”

Section: B Work On Scalable Subgraph Miningmentioning

confidence: 99%

BTLA-LSDG: Blockchain-Based Triune Layered Architecture for Authenticated Subgraph Query Search in Large-Scale Dynamic Graphs

Sharmila¹,

Devi²

2023

IETE Journal of Research

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Over the past era, subgraph mining from a large collection of graph database is a crucial problem. Existing works on subgraph mining is based on the threshold value, which returns similar graphs for a query graph. However, the number of graphs in the answer set for the same threshold can vary in terms of structure and context. In addition, scalability is another big problem due to insufficient storage.Further, it can suffer from security issues. In a distributed environment, since more queries come from different users, it is possible for the attackers to access the graph. These three problems highly exist in the current subgraph mining. To address this downside, our proposed work introduces aBlockchain-based Triune Layered Architecture for authenticated query search in the large scale dynamic graphs. The two fold process is handled in BTLA-LSDG: graph indexing and authenticated query search (query processing), which are implemented in triune layers (Data Generation Layer, Data Storage Layer, and Service Layer). Initially, data owners are authenticated to blockchain using Four-Q-Curve algorithm. The graph index is constructed by data owners and merged graph index is constructed by service providers. Based on the uploaded graph index, hash index is constructed using SHA-3. The hash index is fed into blockchain and form Dendrimer -Fractal Index. On the other hand, data user submits query with authentication. For every authenticated query, the four fold process is handled. Firstly, Multi-Constraint based Belief Entropy function is used for feature sets computation for a given query. Then Dual Similarity based MapReduce helps inmapping and reducing the relevant subgraphs with the use of optimal feature sets. Thirdly, Recurrent Neural Network (RNN)is used for subgraph isomorphic testing. Finally, graph index refinement process is undertaken to improve the query results. For this, query error is computed for each user's query at the end of retrieval. With respect to query error, fuzzy logic is used to refine the index of graph dynamically. This experiment is implemented using Hadoop environment and the results show better efficiency in terms of Scalability, Security and Storage. Further, it is tested with Precision, Recall, F-measure, Accuracy, Error Rate, Query Response Time and Positive Results.

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“…MapReduce-based multiple-subgraph query processing (MSP) was proposed to process multiple graph queries in Hadoop [47]. MSP uses structure-based partitioning and an integrated graph index (IGI) to reduce the query search space.…”

Section: Related Workmentioning

confidence: 99%

Distributed Subgraph Query Processing Using Filtering Scores on Spark

Bok,

Kim,

Lee

et al. 2023

Electronics

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As various services have been generating large-scale graphs to represent multiple relationships between objects, studies have been conducted to obtain subgraphs with particular patterns. In this paper, we propose a distributed query processing method to efficiently search a subgraph for a large graph on Spark. To reduce unnecessary processing costs, the search order is determined by filtering scores using the probability distribution. The partitioned queries are searched in parallel in the distributed graph of each slave node according to the search order, and the local search results obtained from each slave node are combined and returned. The query is partitioned in triplets based on the determined search order. The performance of the proposed method is compared with the performance of existing methods to demonstrate its superiority.

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MSP: Multiple Sub-graph Query Processing using Structure-based Graph Partitioning Strategy and Map-Reduce

Cited by 8 publications

References 16 publications

Evaluation Method of Wushu Teaching Quality Based on Fuzzy Clustering

Evaluation Method of Wushu Teaching Quality Based on Fuzzy Clustering

BTLA-LSDG: Blockchain-Based Triune Layered Architecture for Authenticated Subgraph Query Search in Large-Scale Dynamic Graphs

Distributed Subgraph Query Processing Using Filtering Scores on Spark

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