The upcoming 2nd International Workshop on Inductive Reasoning and Machine Learning for the Semantic Web (IRMLeS), will be held as part of the 7th Extended Semantic Web Conference (ESWC 2010) in Heraklion, Crete (Greece). The primary goal of the workshop is to bring together researchers and practitioners interested in the interdisciplinary research on the intersection of the Semantic Web with Knowledge Discovery and Machine Learning. The workshop is conceived to provide a meeting point for the related communities to stimulate collaboration and enable cross-fertilization of ideas.

Large amounts of data increasingly becoming available and described using real-life ontologies represented in Semantic Web languages, recently opened up the possibility for interesting real-world data mining applications on the Semantic Web. However, exploiting this global resource of data requires new kinds of approaches for data mining and data analysis that would be able to deal at the same time with its scale and with the complexity, expressiveness, and heterogeneity of the representation languages, leverage on availability of ontologies and explicit semantics of the resources, and account for novel assumptions (e.g., “open world”) that underlie reasoning services within the Semantic Web.

The workshop will try to address the above issues, in particular focusing on the problems of how machine learning techniques, such as statistical learning methods and inductive forms of reasoning, can work directly on the richly structured Semantic Web data and exploit the Semantic Web technologies, what is the value added of machine learning methods for the Semantic Web, and what are the challenges for developers of machine learning techniques for the Semantic Web data, for example in the area of ontology mining.


Full-day workshop featuring 
  • invited talks, 
  • presentations (technical, position and application papers) 
  • a late breaking news session and 
  • a wrap-up discussion


The intended audience for this workshop includes:
  • Semantic Web researchers interested in methods for intelligent data analysis and inductive and statistical approximate reasoning
  • Researchers in machine learning and data mining with interest in the Semantic Web technologies
  • Developers of applications of the Semantic Web technologies that contain components realizing inductive and statistical approximate reasoning, data mining and/or machine learning tasks
  • Knowledge engineers and ontology developers interested in semi-automatic methods for ontology mining, namely ontology construction and evolution


The topics of interest of the workshop include, but are not limited to:
  • Knowledge Discovery and Ontologies: data mining techniques using ontologies, ontology mining and knowledge discovery from ontological knowledge bases, ontology-based interpretation and validation of discovered knowledge, evaluation methodologies and metrics for the interaction of knowledge discovery and ontologies, whole knowledge discovery process guided by ontologies
  • Inductive Reasoning with Concept Languages: inductive aggregation, concept retrieval and query answering, approximate classification, inductive methods and fuzzy reasoning for ontology mapping, construction and evolution, concept change and novelty detection for ontology evolution
  • Statistical learning for the Semantic Web: refinement operators for concept and rule languages, concept and rules learning, kernels and instance-based learning for structured representations, semantic (dis )similarity measures and conceptual clustering, probabilistic methods for concept and rule languages
  • Special focus topics: OWA vs CWA in learning, applicability of relational learning in the Semantic Web context, integration of induction and deduction, benchmarking of datasets
  • Applications: (in the domains of the main tracks of ESWC) plus life sciences, cultural heritage, semantic multimedia, geo-informatics, and others