Large-scale graph data management and mining in cloud environments have been a widely discussed issue in recent times. The goal and the scope of this chapter is to discuss how X10 (a Partitioned Global Address Space (PGAS) language) has been applied for programming data-intensive systems. ...
Many graph data sets are defined on massive node domains in which the number of nodes in the underlying domain is very large. As a result, it...doi:10.1007/978-1-4419-6045-0_2Charu C. AggarwalHaixun WangSpringer USCharu Aggarwal and Haixun Wang. Graph data management and mining: A ...
Graph Data Management Techniques & ApplicationsC. E. Tsourakakis. Large scale graph mining with MapReduce: Diameter estimation and eccentricity plots of massive graphs with mining applications. In Social Network Mining, Analysis and Research... CE Tsourakakis - 《Graph Data Management Techniques & ...
Large graph data management and mining in clouds has become an important issue in recent times. We propose Acacia which is a distributed graph database engine for scalable handling of such large graph data. Acacia operates between the boundaries of private and public clouds. Acacia partitions and...
Review Graph Mining A framework of review data mining based on a graph model. 3followers Japan https://rgmining.github.io/ README.md Repositories fraudarPublic A wrapper of FRAUDAR algorithm fraud-eaglePublic An implementation of Fraud Eagle algorithm ...
26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pages 338–348, 2020. [6] Difan Zou, Ziniu Hu, Yewen Wang, Song Jiang, Yizhou Sun, and Quanquan Gu. Layer-dependent importance sampling for training deep and large graph convolutional networks. In Advances in...
An open source, standard data file format for graph data storage and retrieval What is GraphAr? Graph processing serves as the essential building block for a diverse variety of real-world applications such as social network analytics, data mining, network routing, and scientific computing. ...
Graph mining: A survey of graph mining techniques Data mining is comprised of many data analysis techniques. Its basic objective is to discover the hidden and useful data pattern from very large set of dat... RS Ur,KA Ullah,F Simon - International Conference on Digital Information Management ...
Wizard-based GUI and compatibility with Gremlin facilitate easy graph analysis. What's New Application Scenarios Internet Knowledge Graph Financial Risk Control Urban Industry Enterprise IT Internet Suitable for mining valuable information from large and complex social networks. ...
In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2020–2029. ^abXiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu, and Tat-Seng Chua. 2020. Disentangled Graph Collaborative Filtering. In Proceedings of the 43rd International ACM SIGIR...