00839nam0-2200253 --450 991074070050332120230914124047.020230914d1983----kmuy0itay5050 baitafreIT 001yy<<Gli >>illuministi francesiBayle, manoscritti clandestini, Voltaire, Montesquieu, Diderot, D'Alembert, Condillac, Lamettrie, Helvetius, d'Holbach, Rousseau, Turgot, Raynal, Condorceta cura di Pietro Rossi10. ristTorinoLoescher1983XXXI, 378 p.20 cmClassici della filosofiaRossi,Pietro<1930- >ITUNINAREICATUNIMARCBK9910740700503321TT 2792740DDCICDDCICILLUMINISTI francesi477101UNINA01052nam0 22002771i 450 UON0034749820231205104326.72920091125d1969 |0itac50 baengGB|||| 1||||OsborneMartin BanhamEdinburghOliver and Boyd1969109 p.19 cm.001UON003411402001 Writers and critics210 EdinburghLondonOliver and BoydOSBORNE JOHNUONC074518FIGBEdinburghUONL003034823.0109Narrativa inglese. Storia, descrizione, studio critico21BANHAMMartinUONV160390193310Oliver and BoydUONV249052650ITSOL20240220RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00347498SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI Angl VI B OSB BAN SI SI 4079 5 Osborne166085UNIOR04276nam 22006135 450 991048361050332120251226203650.010.1007/b106731(CKB)1000000000212866(SSID)ssj0000318578(PQKBManifestationID)11239154(PQKBTitleCode)TC0000318578(PQKBWorkID)10311158(PQKB)11482275(DE-He213)978-3-540-31841-5(MiAaPQ)EBC3067817(PPN)123092663(BIP)11548152(EXLCZ)99100000000021286620100715d2005 u| 0engurnn|008mamaatxtccrKnowledge Discovery in Inductive Databases Third International Workshop, KDID 2004, Pisa, Italy, September 20, 2004, Revised Selected and Invited Papers /edited by Arno Siebes1st ed. 2005.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2005.1 online resource (VIII, 200 p.) Information Systems and Applications, incl. Internet/Web, and HCI,2946-1642 ;3377Bibliographic Level Mode of Issuance: MonographPrinted edition: 9783540250821 Includes bibliographical references and index.Invited Paper -- Models and Indices for Integrating Unstructured Data with a Relational Database -- Contributed Papers -- Constraint Relaxations for Discovering Unknown Sequential Patterns -- Mining Formal Concepts with a Bounded Number of Exceptions from Transactional Data -- Theoretical Bounds on the Size of Condensed Representations -- Mining Interesting XML-Enabled Association Rules with Templates -- Database Transposition for Constrained (Closed) Pattern Mining -- An Efficient Algorithm for Mining String Databases Under Constraints -- An Automata Approach to Pattern Collections -- Implicit Enumeration of Patterns -- Condensed Representation of EPs and Patterns Quantified by Frequency-Based Measures.The3rdInternationalWorkshoponKnowledgeDiscoveryinInductiveDatabases (KDID 2004) was held in Pisa, Italy, on September 20, 2004 as part of the 15th European Conference on Machine Learning and the 8th European Conference onPrinciplesandPracticeofKnowledgeDiscoveryinDatabases(ECML/PKDD 2004). Ever since the start of the ?eld of data mining, it has been realized that the knowledge discovery and data mining process should be integrated into database technology. This idea has been formalized in the concept of inductive databases, introduced by Imielinski and Mannila (CACM 1996, 39(11)). In general, an inductive database is a database that supports data mining and the knowledge discovery process in a natural and elegant way. In addition to the usual data, it also contains inductive generalizations (e.g., patterns, models) extracted from the data. Within this framework, knowledge discovery is an - teractive process in which users can query the inductive database to gain insight to the data and the patterns and models within that data. Despite many recent developments, there still exists a pressing need to - derstandthecentralissuesininductivedatabases.Thisworkshopaimedtobring together database and data mining researchers and practitioners who are int- ested in the numerous challenges that inductive databases o'ers. This workshop followed the previous two workshops: KDID 2002 held in Helsinki, Finland, and KDID 2003 held in Cavtat-Dubrovnik, Croatia.Information Systems and Applications, incl. Internet/Web, and HCI,2946-1642 ;3377Database managementArtificial intelligenceDatabase ManagementArtificial IntelligenceDatabase management.Artificial intelligence.Database Management.Artificial Intelligence.005.74Goethals Bart973958Siebes Arno1958-1757044MiAaPQMiAaPQMiAaPQBOOK9910483610503321Knowledge discovery in inductive databases4195681UNINA