COMMunity Evaluation and Transformation is the name of an detection algorithm based on the method of Louvain for finding partitioned and overlapping communities in bipartite directed and unipartite graphs.
Detection of communities from observation can help identify trends, make recommendations, offer new services, or facilitate communication. But the issues are not limited to the social sphere, it can be extended to the political sphere with the evolution of the partitioning of voters according to the evolution of the collection of voting intentions. Some other fields of application could be:
- restructuring of services,
- reorganization of entities,
- personalized dissemination,
- common interests center,
- brain connection path,
To take advantages of knowledge models (ontologies) information retrieval systems may use the relationships between concepts to extend or reformulate queries. Our ontology based information retrieval system (OBIRS) relies on a domain ontology and on resources that are indexed using its concepts (e.g. genes annotated by concepts of the Gene Ontology or PubMed articles annotated using the MeSH, Medical Subject Headings). To fully benefit of this system,
queries have to be expressed using concepts of the same ontology. OBIRS’ interface thus provides query formulation assistance through auto-completion and ontology browsing. It then estimates the overall relevance of each resource w.r.t. a given query. The retrieved resources are ordered according to their overall scores, so that the most relevant resources (indexed with the exact query concepts) are ranked higher than the least relevant ones (indexed with hypernyms or hyponyms of query concepts). We provide visual results thanks to pictogram displayed on an interactive semantic map.
Two versions have been developped:
User Centered and Ontology Based Information Retrieval System for Life Sciences
Mohameth-François Sy, Sylvie Ranwez, Jacky Montmain, Armelle Regnault, Michel Crampes, Vincent Ranwez.
In BMC Bioinformatics, 13(Suppl 1):S4, 2012
We also use it in an hybrid approach, that benefits from both lexical and ontological document description, and combines them in a software architecture dedicated to information retrieval and rendering in specific domains. Relevant documents are first identified via their conceptual indexing based on domain ontology, and then segmented to highlight text fragments that deal with users’ information needs.
How ontology based information retrieval systems may benefit from lexical text analysis.
Sylvie Ranwez, Benjamin Duthil, Mohameth François Sy, Jacky Montmain, Patrick Augereau, Vincent Ranwez.
In "New Trends of Research in Ontologies and Lexical Resources", chapter 11, pp. 209-230,
Series: Theory and Applications of Natural Language Processing, Springer, February 2013.
Many applications take advantage of both ontologies and the Linked Data paradigm to characterize various kinds of resources. To fully exploit this knowledge, measures are used to estimate the relatedness of resources regarding their semantic characterization. Such semantic measures, particularly useful for information retrieval in RDF knowledge bases, mainly focus on specific aspects of the semantic characterization (e.g. types) or only partially exploit the semantics expressed in the knowledge base. We proposed a framework for defining semantic measures in the aim of comparing instances defined within an RDF knowledge base and we demonstrated that it is particularly well suited to recommendation systems. An application has been developed dedicated to music band recommendation: http://www.lgi2p.ema.fr:8090/kid/tools/bandrec
Semantic Measures Based on RDF Projections: Application to Content-Based Recommendation Systems online
Sébastien Harispe, Sylvie Ranwez, Stefan Janaqi and Jacky Montmain.
Proceedings of On the Move to Meaningful Internet Systems: OTM 2013 Conferences, ODBase 2013,
Lecture Notes in Computer Science, vol. 8185, Robert Meersman, Hervé Panetto, Tharam Dillon, Johann Eder,
Zohra Bellahsene, Norbert Ritter, Pieter Leenheer, and Deijing Dou eds, isbn : 978-3-642-41029-1,
Springer Berlin Heidelberg, pp. 606-615, Graz, Austria, September 10-12 2013.
Involved in several projects that aim to assist several scientific communities in the management of their members, we developped collaborative platform:
For the Cancer community we also developped Kalitmo, a set of additional tools that provide some vues on the community: people involved, geo-localisation of scientific teams, statistics regarding their activity (publication, pattents, etc.). http://itcancer.mines-ales.fr
Organization of a French tutorial dedicated to the SML (Semantic Measures Library) within the 25th IC French conference (Ingénierie des Connaissances / Knowledge Engineering), Clermont Ferrand, France, May, 12. 2014.
Organization of the 21th French IC conference (Ingénierie des Connaissances / Knowledge Engineering), in Nîmes from 8th to 12th of June 2010.