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Applications and Kernels>
- General sources of information
- Bipartite Matching: Given a graph with two classes of vertices, find an edge subset that connects each of one class vertex to exactly one of the other class.
- Breadth First Search: explore graph from a root vertex
- Centrality: fining the "most important" vertices
- Community Detection: Finding subgraphs with some affinity
- Connected Components: subgraphs where all vertices are reachable
- Graph Systems
- Higher Order Networks
- Jaccard: compute fraction of neighbor's in common between two vertices
- Non-Obvious Relationship Analysis: variation of Jaccard with extra search constraints
- Page Rank: estimate ``connectiveness'' or centrality of a vertex
- Shortest Path. Find shortest paths between (specific vertex, all vertices) to (specific vertex, all other vertices)
- Spanning Trees: See also BFS
- See book Chap. 3, esp. 3-10 and 11-4 Algorithm 2
- Wikipedia: Kruskal's Algorithm for weighted edges
- Stateful Random Walks
Sample Graph Data Sets
- SNAP: Stanford Large Network Dataset Collection. Wide spectrum of a variety of graph types of various sizes.
- Sample datasets formatted for Neo4j language
- Amazon-hosted Data sets for the Graph Challenge project. Includes pointers to multiple graph generators.
- A Python bipartite graph generator written by Jeremy Speth at ND in summer 2018.
- Hyperlink graphs<\a>
- Neural Connectome Data
- Network Data
- ICON: Colorado Index of Complex Networks
- KONECT: Koblenz Network Collection
- Network Repository "Wide variety of applications and domains (e.g., network science, bioinformatics, machine learning, data mining, physics, and social science) and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data."
- Data set for Higher Order Networks. Same gihhub site has code to generate synthetic HON graphs
Programming Paradigms
Wikipedia:
For IEEE Xplore papers, first connect to IEEE Xplore in another tab or window and then
access the link. ND students can connect to IEEE Xplore through the Engineering Library
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