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020 _a9783319457635
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024 7 _a10.1007/978-3-319-45763-5
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072 7 _aUNF
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072 7 _aUYQE
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082 0 4 _a006.312
_223
245 1 0 _aAdvances in Knowledge Discovery and Management
_h[electronic resource] :
_bVolume 6 /
_cedited by Fabrice Guillet, Bruno Pinaud, Gilles Venturini.
250 _a1st ed. 2017.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _aXXI, 278 p. 81 illus., 61 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
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347 _atext file
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490 1 _aStudies in Computational Intelligence,
_x1860-9503 ;
_v665
505 0 _aPart I: Online learning of a weighted selective naive Bayes classifier with non-convex optimization -- On making skyline queries resistant to outliers -- Adaptive Down-Sampling and Dimension Reduction in Time Elastic Kernel Machines for Efficient Recognition of Isolated Gestures -- Exact and Approximate Minimal Pattern Mining -- Part II: Comparison of proximity measures for a topological discrimination -- Comparison of linear modularization criteria using the relational formalism, an approach to easily identify resolution limit -- A novel approach to feature selection based on quality estimation metrics -- Ultrametricity of Dissimilarity Spaces and Its Significance for Data Mining -- Part III: SMERA: Semantic Mixed Approach for Web Query Expansion and Reformulation -- Multi-layer ontologies for integrated 3D shape segmentation and annotation -- Ontology Alignment Using Web Linked Ontologies as Background Knowledge -- LIAISON: reconciLIAtion of Individuals profiles across SOcial Networks -- Clustering of Links and Clustering of Nodes: Fusion of Knowledge in Social Networks.
520 _aThis book presents a collection of representative and novel work in the field of data mining, knowledge discovery, clustering and classification, based on expanded and reworked versions of a selection of the best papers originally presented in French at the EGC 2014 and EGC 2015 conferences held in Rennes (France) in January 2014 and Luxembourg in January 2015. The book is in three parts: The first four chapters discuss optimization considerations in data mining. The second part explores specific quality measures, dissimilarities and ultrametrics. The final chapters focus on semantics, ontologies and social networks. Written for PhD and MSc students, as well as researchers working in the field, it addresses both theoretical and practical aspects of knowledge discovery and management.
650 0 _aData mining.
_93907
650 0 _aComputational intelligence.
_97716
650 0 _aArtificial intelligence.
_93407
650 1 4 _aData Mining and Knowledge Discovery.
_962515
650 2 4 _aComputational Intelligence.
_97716
650 2 4 _aArtificial Intelligence.
_93407
700 1 _aGuillet, Fabrice.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_962516
700 1 _aPinaud, Bruno.
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_962517
700 1 _aVenturini, Gilles.
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710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
_z9783319833682
830 0 _aStudies in Computational Intelligence,
_x1860-9503 ;
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856 4 0 _uhttps://doi.org/10.1007/978-3-319-45763-5
912 _aZDB-2-ENG
912 _aZDB-2-SXE
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