# Graph Data Analysis Task

(Redirected from Graph Mining)

A Graph Data Analysis Task is a relational data analysis task whose task input is a graph dataset.

**AKA:**Graph Mining.**Context:****output:**a Network Analysis Report/[Graph Analysis Report]] (which mentions discovered Graph Patterns/Network Patterns).- It can be solved by a Graph Mining System (that implements graph mining algorithms/network analysis algorithms).
- It can range from being an Undirected Graph Analysis Task to being a Directed Graph Analysis Task.
- It can range from being a Graph Node Analysis Task (such as graph node classification) to being a Graph Edge Analysis Task (such as: graph edge label classification).
- It can range from being a Single-Graph Analysis Task to being a Multi-Graph Analysis Task.
- It can be supported by a Graph Data Processing Task.
- It can range from being:
- …

**Example(s):**- a Social Network Mining Task (of a social network dataset), such as a Co-Authorship Analysis Task.
- a Bibliometric Analysis Task (of a bibliographic network), such as a Citation Network Analysis Task (of a citation network dataset).
- a Biological Network Analysis Task (of a biological network dataset), such as: a Protein Interaction Network Analysis Task.
- a WWW Network Analysis Task.
- …

**Counter-Example(s):****See:**Web Mining Task; Graph Theory; Greedy Search Approach of Graph Mining; Inductive Database Search Approach of Graph Mining; Kernel-Based Approach of Graph Mining; Tree Mining; Collective Classification; Entity Resolution; Graph Clustering; Graph Mining; Group Detection; Inductive Logic Programming; Link Prediction; Relational Learning.

## References

### 2011

- (Chakrabarti, 2011) ⇒ Deepayan Chakrabarti. (2011). “Graph Mining.” In: (Sammut & Webb, 2011) p.469
- (Geetor, 2011) ⇒ Lise Getoor. (2011). “Link Mining and Link Discovery.” In: (Sammut & Webb, 2011) p.606

### 2005

- (Getoor & Diehl, 2005) ⇒ Lise Getoor, and Christopher P. Diehl. (2005). “Link Mining: A survey.” In: [[SIGKDD Explorations], 7(2).
*Link mining*is a newly emerging research area that is at the intersection of the work in link analysis [58; 40], hypertext and web mining [16], relational learning and inductive logic programming [38], and graph mining [23]. We use the term link mining to put a special emphasis on the links - moving them up to first-class citizens in the data analysis endeavor. In recent years, there have been several workshop series devoted to topics related to link mining. One of the earliest workshops was the 1998 AAAI Fall Symposium on AI and Link Analysis [58]. Other workshop series include the workshops on Statistical Relational Learning [48; 49; 28], Multi-Relational Data Mining [65; 39; 36; 37], LinkKDD [35; 1; 3], Link Analysis, Counter-terrorism and Security [104; 26; 103], and Mining Graphs, Trees and Sequences [94; 66; 85].