Graph Mining and Network Analysis
Graph Mining and Network Analysis are fields of study that focus on extracting valuable insights from graph-structured data. Graphs are mathematical structures that represent relationships between entities, with nodes representing entities and edges representing relationships between them.Graph Mining involves applying data mining techniques to analyze large-scale graphs to discover patterns, structures, and trends. This can include identifying communities or clusters of nodes, detecting anomalies or outliers, and predicting missing links or future connections.Network Analysis, on the other hand, focuses on the study of networks to understand their structure, dynamics, and properties. It involves analyzing network topologies, centrality measures, and connectivity patterns to gain insights into the behavior of complex systems.Applications of Graph Mining and Network Analysis are diverse and include social network analysis, biological network analysis, transportation network analysis, and more.
Related Conference of Graph Mining and Network Analysis
12th World Congress on Computer Science, Machine Learning and Big Data
6th International Conference on Renewable Energy and Resources
12th International Conference and Exhibition on Mechanical & Aerospace Engineering
25th International Conference on Big Data & Data Analytics
Graph Mining and Network Analysis Conference Speakers
Recommended Sessions
- Big Data Analytics in Finance and Banking
- Big Data Security and Privacy
- Big Data Technologies and Tools session
- Case studies and best practices in Big Data Analytics
- Clustering and Association Rule Mining
- Data Cleaning and Preprocessing
- Deep Learning for Big Data Applications
- Exploratory Data Analysis (EDA)
- Foundations of Big Data Analysis
- Future Trends in Big Data Analysis and Data Mining
- Graph Mining and Network Analysis
- Machine Learning for Big Data
- Privacy-Preserving Data Mining
- Real Time Big Data Processing
- Recommender Systems and Personalization
- Social Network Analysis
- Stream Data Mining and Sensor Data Analysis
- Text Mining and Natural Language Processing
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