Managing and Mining Graph Data

Target entity: Managing and Mining Graph Data
Context triple: [Charu C. Aggarwal, notableWork, Managing and Mining Graph Data]

• A. Mining of Massive Datasets
  "Mining of Massive Datasets" is a widely used textbook that introduces practical and scalable data mining and machine learning techniques for analyzing large-scale datasets.
• B. Data Mining: Concepts and Techniques
  Data Mining: Concepts and Techniques is a widely used academic textbook that systematically introduces the principles, algorithms, and practical methods of data mining and knowledge discovery from large datasets.
• C. Graph Algorithms (book)
  "Graph Algorithms" is a foundational textbook by Shimon Even that systematically presents the theory, design, and analysis of algorithms for solving fundamental problems on graphs.
• D. Top 10 algorithms in data mining
  "Top 10 algorithms in data mining" is a widely cited survey paper that summarizes and evaluates the most influential data mining algorithms across key tasks such as classification, clustering, and association analysis.
• E. GraphX
  GraphX is Apache Spark’s distributed graph processing framework that enables large-scale graph computation and analysis using Spark’s resilient distributed datasets (RDDs).
• F. None of above. chosen
• G. Unsure - the case is ambiguous/there is not enough information to decide.

Target entity: Managing and Mining Graph Data
Target entity description: Managing and Mining Graph Data is a comprehensive technical book that surveys fundamental concepts, algorithms, and applications in the analysis and processing of graph-structured data.

• A. Mining of Massive Datasets
  "Mining of Massive Datasets" is a widely used textbook that introduces practical and scalable data mining and machine learning techniques for analyzing large-scale datasets.
• B. Data Mining: Concepts and Techniques
  Data Mining: Concepts and Techniques is a widely used academic textbook that systematically introduces the principles, algorithms, and practical methods of data mining and knowledge discovery from large datasets.
• C. Graph Algorithms (book)
  "Graph Algorithms" is a foundational textbook by Shimon Even that systematically presents the theory, design, and analysis of algorithms for solving fundamental problems on graphs.
• D. Top 10 algorithms in data mining
  "Top 10 algorithms in data mining" is a widely cited survey paper that summarizes and evaluates the most influential data mining algorithms across key tasks such as classification, clustering, and association analysis.
• E. GraphX
  GraphX is Apache Spark’s distributed graph processing framework that enables large-scale graph computation and analysis using Spark’s resilient distributed datasets (RDDs).
• F. None of above. chosen