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Section: Software

Data Mining

Classification and Clustering Methods

Participants : Marc Csernel, Yves Lechevallier [co-correspondant] , Brigitte Trousse [co-correspondant] .

We developed and maintained a collection of clustering and classification software, written in C++ and/or Java:

Supervised methods

Unsupervised methods : partioning methods

Unsupervised methods : agglomerative methods

A Web interface developed in C++ and running on our Apache internal Web available for the following methods: SCluster, Div, yCdis, CCClust.

Previous versions of the above software have been integrated in the SODAS 2 Software  [98] which was the result of the european project ASSO (ASSO: Analysis System of Symbolic Official data) (2001-2004). SODAS 2 softsodaslinkware supports the analysis Stof multidimensional complex data (numerical and non numerical) coming from databases mainly in statistical offices and administration using Symbolic Data Analysis [82] . This software is registrated at APP. The latest executive version of the SODAS 2 software, with its user manual can be downloaded at [88] , [112] .

Extracting Sequential Patterns with Low Support

Participant : Brigitte Trousse [correspondant] .

Two methods for extracting sequential patterns with low support have been developed by D. Tanasa in his thesis (see Chapter 3 in [108] for more details) in collaboration with F. Masseglia and B. Trousse :

Mining Data Streams

Participants : Brigitte Trousse [correspondante] , Mohamed Gaieb.

In Marascu's thesis (2009) [95] , a collection of software have been developed for knowledge discovery and security in data streams. Three clustering methods for mining sequential patterns (Java) in data streams method have been developped in Java:

Such methods take batches of data in the format "Client-Date-Item" and provide clusters of sequences and their centroids in the form of an approximate sequential pattern calculated with an alignment technique.

In 2010 the Java code of one method called SCDS has been integrated in the MIDAS demonstrator (cf. 8.2.1 ) and a C++ version has been implemented by F. Masseglia for the CRE contract with Orange Labs with the deliverability of a licence) with a visualisation module (in Java).

It has been tested on the following data:

This year it has been integrated as a Web service (Java version) in the first version of FocusLab platform in the ELLIOT context (cf. 6.5.2 ): a demonstration was made on San Rafaelle Hospital media use case at the first ELLIOT review at Brussels (cf. ).