ESWC'11 Proceedings of the 8th extended semantic web conference on The semantic web: research and applications - Volume Part I
DC proposal: ontology learning from noisy linked data
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part II
Unsupervised generation of data mining features from linked open data
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
An approach to parallel class expression learning
RuleML'12 Proceedings of the 6th international conference on Rules on the Web: research and applications
Discovering interesting information with advances in web technology
ACM SIGKDD Explorations Newsletter
AMIE: association rule mining under incomplete evidence in ontological knowledge bases
Proceedings of the 22nd international conference on World Wide Web
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Nowadays, building ontologies is a time consuming task since they are mainly manually built. This makes hard the full realization of the Semantic Web view. In order to overcome this issue, machine learning techniques, and specifically inductive learning methods, could be fruitfully exploited for learning models from existing Web data. In this paper we survey methods for (semi-)automatically building and enriching ontologies from existing sources of information such as Linked Data, tagged data, social networks, ontologies. In this way, a large amount of ontologies could be quickly available and possibly only refined by the knowledge engineers. Furthermore, inductive incremental learning techniques could be adopted to perform reasoning at large scale, for which the deductive approach has showed its limitations. Indeed, incremental methods allow to learn models from samples of data and then to refine/enrich the model when new (samples of) data are available. If on one hand this means to abandon sound and complete reasoning procedures for the advantage of uncertain conclusions, on the other hand this could allow to reason on the entire Web. Besides, the adoption of inductive learning methods could make also possible to dial with the intrinsic uncertainty characterizing the Web, that, for its nature, could have incomplete and/or contradictory information.