You are here

KDDLab research produced a number of free opensource data mining software, such as: [list] [*] [b]Trajectory Pattern Miner[/b]: Data mining tool for the extraction of spatio-temporal frequent patterns from GPS traces of moving objects. [url=]Sourceforge[/url] [*] [b]Never Walk Alone[/b]: Exploiting spatial location uncertainty for ensuring anonymity in moving objects databases. [url=]Website[/url] [*] [b]Temporally Annotated Sequences[/b]: Data mining tool for the extraction of sequential patterns with typical transition times between elements of the sequences. [*] [b]Daedalus[/b]: Knowledge Discovery support environment for data mining queries on mobility data. [*] [b]Athena[/b]: Semantic enrichment environment for trajectories and pattern intepretation and understanding. athena has been integrated with Daedalus thus provinding a complete tool for data mining querying and reasoning. [*] [b]T-Cluster[/b]: density-based clustering algorithm to discover set of similar trajectories, according to a repertoire of trajectory similarity functions [*] [b]WhereNext[/b]: tool for the prediction of the next location of a moving object, which uses the previous movements of all objects in a certain area to learn a classifier. [*] [b]GERM[/b]: the Graph Evolution Rule Miner: given a set of temporal snapshots of the same single graph, this miner finds all the evolution patterns more frequent than a given threshold minfreq, and no bigger than a given threshold maxsize, from which we can compute rules of evolution, together with their support and confidence. [*] [b]GAMP[/b], the Graph Antimonotone-Monotone Pruner: given a dataset of graphs, a threshold of frequency minfreq and a conjunction of monotone and antimonotone constraints, this preprocessor performs a loop of pruning and returns a dataset of graphs where each graph satisfies the monotone constraints, and each edge is frequent and satisfies the antimonotone constraints. [*] [b]M-Atlas[/b] M-Atlas is a mobility querying and data mining system centered onto the concept of trajectory. Besides the mechanisms for storing and querying trajectory data, M-Atlas has mechanisms for mining trajectory patterns and models that, in turn, can be stored and queried. [url=]Website[/url] [*] [b]SMA[/b] Sequence Mining Automata: a new techniques for mining frequent sequences under regular expressions. [url=]Website[/url] [*] [b]BF-P2KA[/b] BF-2PkA is an algorithm for anonymizing sequence data. It transforms a sequence dataset in a k-anonymous version while preserving the sequential pattern mining analysis. [url=]Sourceforge[/url] [/list]