Machine Learning and Knowledge Discovery in Databases [electronic resource] :European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part I /
Contributor(s): Calders, Toon [editor.] | Esposito, Floriana [editor.] | Hüllermeier, Eyke [editor.] | Meo, Rosa [editor.] | SpringerLink (Online service).Material type: BookSeries: Lecture Notes in Computer Science: 8724Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.Description: XLIV, 709 p. 183 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783662448489.Subject(s): Computer science | Data mining | Information storage and retrieval | Artificial intelligence | Pattern recognition | Computer Science | Data Mining and Knowledge Discovery | Artificial Intelligence (incl. Robotics) | Pattern Recognition | Information Storage and RetrievalOnline resources: Click here to access online
Dynamic networks and knowledge discovery -- Interactions between data mining and natural language processing -- Mining ubiquitous and social environments -- Statistically sound data mining -- Machine learning for urban sensor data -- Multi-target prediction -- Representation learning -- Neural connectomics: from imaging to connectivity -- Data analytics for renewable energy integration -- Linked data for knowledge discovery -- New frontiers in mining complex patterns -- Experimental economics and machine learning -- Learning with multiple views: applications to computer vision and multimedia mining -- Generalization and reuse of machine learning models over multiple contexts -- Predictive web analytics.
This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.