Inhalt des Dokuments
akt-software
| name | short description | links |
|---|---|---|
| Graphana | A tool for analyzing the combinatorial structure of graphs by computation and estimation of various graph parameters. | |
| Incremental Graph Coloring | An implementation of serveral commonly used heuristic algorithms for the (vertex) graph coloring problem together with a new proposed search tree based algorithm that is based on "incremental coloring". | |
| kconsens | Tool for computing Kemeny rankings by using efficient polynomial-time data reduction rules combined with several exact algorithms. Can solve meaningful real-world instances with more than 100 candidates within milliseconds. | |
| mu-clique | Tool for computing maximum mu-cliques. | |
| s-plex | Tool for finding maximum s-plexes. | |
| Temporal cliques | Tool for enumerating all maximal cliques in a temporal graph | |
| Pattern-Guided k-Anonymity | Heuristic and exact ILP implementation to solve Pattern-Guided k-Anonymity. The collection includes the scripts and datasets used in the paper. | |
| Lobbying | Heuristic and exact ILP implementation including the random instance generator. Binaries are created on 64bit Debian. | |
| Co-Clustering | Implementations of both the naive and the cluster boundary based SAT-Solving approach. | |
| Parliamentary voting procedures | Implementations for both Manipulation and Agenda Control for the amendment procedure and the successive procedure. | |
| Highly Connected Deletion | This package contains the source and the test data for a solver for the Highly Connected Deletion problem. | |
| Well-connected 2-club | Tool for finding well-connected 2-clubs. The implementation can find the support the t-robust, t-hereditary, and the t-connected 2-club model. | |
| DTW Mean | Implementation of a Dynamic Program computing a mean of time series in dynamic time warping spaces. | |
| Maximum Matching | Implementations of both weighted and unweighted reduction rules for maximum matching. | |
| Dynamic Temporal Graph Warping | Implementation of the dtgw-distance algorithms. |