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| Fællesskabsdetektion× | Sekventiel mønsterudvinding× | |
|---|---|---|
| Fagområde≠ | Netværksanalyse | Maskinlæring |
| Familie≠ | Process / pipeline | Machine learning |
| Oprindelsesår≠ | 2002–2019 (algorithm family) | 1995 |
| Ophavsperson≠ | Louvain: Blondel et al. (2008); Leiden: Traag et al. (2019); Girvan-Newman: Girvan & Newman (2002); Infomap: Rosvall & Bergstrom (2008) | Rakesh Agrawal & Ramakrishnan Srikant |
| Type≠ | Graph-partitioning / clustering algorithm family | Unsupervised pattern discovery |
| Oprindelig kilde≠ | Blondel, V.D., Guillaume, J.-L., Lambiotte, R. & Lefebvre, E. (2008). Fast Unfolding of Communities in Large Networks. Journal of Statistical Mechanics, 2008(10), P10008. DOI ↗ | Agrawal, R., & Srikant, R. (1995). Mining sequential patterns. IEEE International Conference on Data Engineering (ICDE), 3–14. DOI ↗ |
| Aliasser≠ | graph clustering, network partitioning, Topluluk Tespiti (Louvain, Girvan-Newman, Leiden) | Sequence Pattern Mining, Sequential Data Mining, Temporal Pattern Mining, Ardışık Örüntü Madenciliği |
| Relaterede≠ | 5 | 3 |
| Resumé≠ | Community detection is a family of graph-partitioning algorithms that discover densely connected sub-groups — communities — within a network. First formalised through the modularity measure by Girvan and Newman (2002), the field advanced rapidly with the Louvain method (Blondel et al., 2008), the Leiden refinement (Traag et al., 2019), and the information-theoretic Infomap approach. All variants answer the same question: which nodes cluster together more tightly among themselves than with the rest of the network? | Sequential Pattern Mining discovers ordered patterns that recur across multiple event sequences in a database. Introduced by Agrawal and Srikant in 1995, it extends association-rule mining to time-ordered transactions. A pattern is frequent when it appears as an ordered subsequence in at least a user-specified fraction of all sequences. The method is widely applied wherever the order of events carries meaning, such as customer purchase histories, clickstream logs, electronic health records, and DNA sequence analysis. |
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