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Automatic multi-partite graph generation from arbitrary data
Affiliation:1. Database Laboratory, Universidade da Coruña, Facultade de Informática, Campus de Elviña s/n, 15071 A Coruña, Spain;2. Yahoo Labs, Barcelona & DTIC, Universitat Pompeu Fabra, Barcelona, Spain;3. DAMA-UPC, Universitat Politèecnica de Catalunya, Campus Diagonal Nord, Building C6, C. Jordi Girona, 1-3, 08034 Barcelona, Spain;1. School of Communication and Electronic Engineering, Qingdao Technological University, Qingdao 266033, PR China;2. Department of Computing, Curtin University, Perth, WA 6102, Australia;3. School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310027, PR China;1. Gran Sasso Science Institute, L’Aquila, Italy;2. University of L’Aquila, L’Aquila, Italy;3. Karlsruhe Institute of Technology, Karlsruhe, Germany;1. Computer Architecture and Communication Area, University Carlos III, Madrid, Spain;2. Argonne National Laboratory, Chicago, USA;3. Bioengineering and Aerospace Engineering Department, University Carlos III, Madrid, Spain;4. Instituto de Investigacion Sanitaria Gregorio Marañon (IiSGM), Madrid, Spain;5. Centro de Investigacion en Red de Salud Mental (CIBERSAM), Madrid, Spain
Abstract:In this paper we present a generic model for automatic generation of basic multi-partite graphs obtained from collections of arbitrary input data following user indications. The paper also presents GraphGen, a tool that implements this model. The input data is a collection of complex objects composed by a set or list of heterogeneous elements. Our tool provides a simple interface for the user to specify the types of nodes that are relevant for the application domain in each case. The nodes and the relationships between them are derived from the input data through the application of a set of derivation rules specified by the user. The resulting graph can be exported in the standard GraphML format so that it can be further processed with other graph management and mining systems. We end by giving some examples in real scenarios that show the usefulness of this model.
Keywords:Graph processing and analysis  Automatic graph generation
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