LEADER 03110nam 2200433 450 001 9910156515103321 005 20230325185645.0 010 $a3-03842-287-8 035 $a(CKB)3710000000987290 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/60288 035 $a(NjHacI)993710000000987290 035 $a(EXLCZ)993710000000987290 100 $a20230325d2016 uy 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aSurface Chemistry and Catalysis /$fedited by Michalis Konsolakis 210 1$aBasel :$cMDPI - Multidisciplinary Digital Publishing Institute,$d2016. 215 $a1 electronic resource (XX, 280 p.) 311 $a3-03842-286-X 327 $aMichalis Konsolakis -- Jesu?s Gonza?lez-Cobos and Antonio de Lucas-Consuegra -- Wendi Sapp, Ranjit Koodali and Dmitri Kilin -- Wenju Wang, Guoping Wang and Minhua Shao -- Lukasz Kubiak, Roberto Matarrese, Lidia Castoldi, Luca Lietti, Marco Daturi and Pio Forzatti -- Eftichia Papadopoulou and Theophilos Ioannides -- Michalis Konsolakis, Zisis Ioakimidis, Tzouliana Kraia and George E. Marnellos -- Antonios Tribalis, George D. Panagiotou, Kyriakos Bourikas, Labrini Sygellou, Stella Kennou, Spyridon Ladas, Alexis Lycourghiotis and Christos Kordulis -- Luis Lopez, Jorge Velasco, Vicente Montes, Alberto Marinas, Saul Cabrera, Magali Boutonnet and Sven Ja?ra?s -- Ana Raquel de la Osa, Amaya Romero, Fernando Dorado, Jose? Luis Valverde and Paula Sa?nchez -- Hui-Zhen Cui, Yu Guo, Xu Wang, Chun-Jiang Jia and Rui Si -- Yeusy Hartadi, R. Ju?rgen Behm and Daniel Widmann -- Lu Qiu, Yun Wang, Dandan Pang, Feng Ouyang, Changliang Zhang and Gang Cao -- Tong Liu, Haiyang Cheng, Weiwei Lin, Chao Zhang, Yancun Yu and Fengyu Zhao-- Xiaoting Li, Pingping Jiang, Zhuangqing Wang and Yuandan Huang. 330 $aSummary/Description for Distribution Channels: The present printed edition of the Special Issue ?Surface Chemistry and Catalysis? published in Catalysts aims to cover some of the recent advances in the field of heterogeneous catalysis that can be obtained by means of advanced characterization techniques, computational calculations and time-resolved methods, with particular emphasis on structure?activity relationships (SARs). It consists of 14 high-quality theoretical and experimental studies on various aspects on catalysis, involving the electrochemical promotion in catalysis, H2O dissociation, H2 production, Fisher?Tropsch synthesis, CO oxidation, among others. 606 $aSurface chemistry 606 $aHeterogeneous catalysis 610 $aadvanced characterization techniques 610 $aheterogeneous catalysis and surface science 610 $acomputational studies 615 0$aSurface chemistry. 615 0$aHeterogeneous catalysis. 676 $a541.33 702 $aKonsolakis$b Michalis 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910156515103321 996 $aSurface Chemistry and Catalysis$91930858 997 $aUNINA LEADER 03799nam 2200445 450 001 9910795609103321 005 20230629233308.0 010 $a1-61249-673-3 010 $a1-61249-671-7 035 $a(CKB)5590000000549530 035 $a(MiAaPQ)EBC6513017 035 $a(EXLCZ)995590000000549530 100 $a20211204d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aParoimia $eBrusantino, Florio, Sarnelli, and Italian proverbs from the sixteenth and seventeenth centuries /$fDaniela D'Eugenio 210 1$aWest Lafayette, Indiana :$cPurdue University Press,$d[2021] 210 4$dİ2021 215 $a1 online resource (573 pages) 311 $a1-61249-674-1 327 $aIntroduction : Literary history and theroies of paremias -- Vincenzo Brusantino's Le cento novelle : paremias and Tridentine ethics in reinterpreting the Decameron -- John Florio's Firste Fruites and Second Frutes : paremias and Elizabethan teaching of the Italian language -- Pompeo Sarnelli's Posilecheata : paremias and the multi-faceted Neapolitan Baroque -- Conclusion -- Index of paremias in Le cento novelle, Firste fruites, seond frutes, and Posilecheata. 330 $a"Proverbs constitute a rich archive of historical, cultural, and linguistic significance that affect genres and linguistics codes. They circulate through writers, texts, and communities in a process that ultimately results in modifications in their structure and meanings. Hence, context plays a crucial role in defining proverbs as well as in determining their interpretation. Vincenzo Brusantino's Le cento novelle (1554), John Florio's Firste Fruites (1578) and Second Frutes (1591), and Pompeo Sarnelli's Posilecheata (1684) offer clear representations of how traditional wisdom and communal knowledge reflect the authors' personal perspectives on society, culture, and literature. The analysis of the three authors' proverbs through comparisons with classical, medieval, and early modern collections of maxims and sententiae provides insights on the fluidity of such expressions, and illustrates the tight relationship between proverbs and sociocultural factors. Brusantino's proverbs introduce ethical interpretations to the one hundred novellas of Boccaccio's The Decameron, which he rewrites in octaves of hendecasyllables. His text appeals to Counter-Reformation society and its demand for a comprehensible and immediately applicable morality. In Florio's two bilingual manuals, proverbs fulfill a need for language education in Elizabethan England through authentic and communicative instruction. Florio manipulates the proverbs' vocabulary and syntax to fit the context of his dialogues, best demonstrating the value of learning Italian in a foreign country. Sarnelli's proverbs exemplify the inherent creative and expressive potentialities of the Neapolitan dialect vis-a?-vis languages with a more robust literary tradition. As moral maxims, ironic assessments, or witty insertions, these proverbs characterize the Neapolitan community in which the fables take place"--$cProvided by publisher. 606 $aProverbs, Italian$xHistory and criticism 606 $aItalian literature$y16th century$xHistory and criticism 606 $aItalian literature$y17th century$xHistory and criticism 615 0$aProverbs, Italian$xHistory and criticism. 615 0$aItalian literature$xHistory and criticism. 615 0$aItalian literature$xHistory and criticism. 676 $a850.9 700 $aD'Eugenio$b Daniela$01504788 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910795609103321 996 $aParoimia$93733997 997 $aUNINA LEADER 05390nam 22007094a 450 001 9911020006703321 005 20200520144314.0 010 $a9786610740208 010 $a9781280740206 010 $a1280740205 010 $a9780470073049 010 $a0470073047 010 $a9780470073032 010 $a0470073039 035 $a(CKB)1000000000355097 035 $a(EBL)284362 035 $a(OCoLC)437176195 035 $a(SSID)ssj0000203339 035 $a(PQKBManifestationID)11174117 035 $a(PQKBTitleCode)TC0000203339 035 $a(PQKBWorkID)10258874 035 $a(PQKB)11441425 035 $a(MiAaPQ)EBC284362 035 $a(PPN)185060625 035 $a(Perlego)2771486 035 $a(EXLCZ)991000000000355097 100 $a20060413d2007 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aMining graph data /$fedited by Diane J. Cook, Lawrence B. Holder 210 $aHoboken, N.J. $cWiley-Interscience$dc2007 215 $a1 online resource (501 p.) 300 $aDescription based upon print version of record. 311 08$a9780471731900 311 08$a0471731900 320 $aIncludes bibliographical references and index. 327 $aMINING GRAPH DATA; CONTENTS; Preface; Acknowledgments; Contributors; 1 INTRODUCTION; 1.1 Terminology; 1.2 Graph Databases; 1.3 Book Overview; References; Part I GRAPHS; 2 GRAPH MATCHING-EXACT AND ERROR-TOLERANT METHODS AND THE AUTOMATIC LEARNING OF EDIT COSTS; 2.1 Introduction; 2.2 Definitions and Graph Matching Methods; 2.3 Learning Edit Costs; 2.4 Experimental Evaluation; 2.5 Discussion and Conclusions; References; 3 GRAPH VISUALIZATION AND DATA MINING; 3.1 Introduction; 3.2 Graph Drawing Techniques; 3.3 Examples of Visualization Systems; 3.4 Conclusions; References 327 $a4 GRAPH PATTERNS AND THE R-MAT GENERATOR4.1 Introduction; 4.2 Background and Related Work; 4.3 NetMine and R-MAT; 4.4 Experiments; 4.5 Conclusions; References; Part II MINING TECHNIQUES; 5 DISCOVERY OF FREQUENT SUBSTRUCTURES; 5.1 Introduction; 5.2 Preliminary Concepts; 5.3 Apriori-based Approach; 5.4 Pattern Growth Approach; 5.5 Variant Substructure Patterns; 5.6 Experiments and Performance Study; 5.7 Conclusions; References; 6 FINDING TOPOLOGICAL FREQUENT PATTERNS FROM GRAPH DATASETS; 6.1 Introduction; 6.2 Background Definitions and Notation 327 $a6.3 Frequent Pattern Discovery from Graph Datasets-Problem Definitions6.4 FSG for the Graph-Transaction Setting; 6.5 SIGRAM for the Single-Graph Setting; 6.6 GREW-Scalable Frequent Subgraph Discovery Algorithm; 6.7 Related Research; 6.8 Conclusions; References; 7 UNSUPERVISED AND SUPERVISED PATTERN LEARNING IN GRAPH DATA; 7.1 Introduction; 7.2 Mining Graph Data Using Subdue; 7.3 Comparison to Other Graph-Based Mining Algorithms; 7.4 Comparison to Frequent Substructure Mining Approaches; 7.5 Comparison to ILP Approaches; 7.6 Conclusions; References; 8 GRAPH GRAMMAR LEARNING; 8.1 Introduction 327 $a8.2 Related Work8.3 Graph Grammar Learning; 8.4 Empirical Evaluation; 8.5 Conclusion; References; 9 CONSTRUCTING DECISION TREE BASED ON CHUNKINGLESS GRAPH-BASED INDUCTION; 9.1 Introduction; 9.2 Graph-Based Induction Revisited; 9.3 Problem Caused by Chunking in B-GBI; 9.4 Chunkingless Graph-Based Induction (Cl-GBI); 9.5 Decision Tree Chunkingless Graph-Based Induction (DT-ClGBI); 9.6 Conclusions; References; 10 SOME LINKS BETWEEN FORMAL CONCEPT ANALYSIS AND GRAPH MINING; 10.1 Presentation; 10.2 Basic Concepts and Notation; 10.3 Formal Concept Analysis 327 $a10.4 Extension Lattice and Description Lattice Give Concept Lattice10.5 Graph Description and Galois Lattice; 10.6 Graph Mining and Formal Propositionalization; 10.7 Conclusion; References; 11 KERNEL METHODS FOR GRAPHS; 11.1 Introduction; 11.2 Graph Classification; 11.3 Vertex Classification; 11.4 Conclusions and Future Work; References; 12 KERNELS AS LINK ANALYSIS MEASURES; 12.1 Introduction; 12.2 Preliminaries; 12.3 Kernel-based Unified Framework for Importance and Relatedness; 12.4 Laplacian Kernels as a Relatedness Measure; 12.5 Practical Issues; 12.6 Related Work 327 $a12.7 Evaluation with Bibliographic Citation Data 330 $aThis text takes a focused and comprehensive look at mining data represented as a graph, with the latest findings and applications in both theory and practice provided. Even if you have minimal background in analyzing graph data, with this book you'll be able to represent data as graphs, extract patterns and concepts from the data, and apply the methodologies presented in the text to real datasets. There is a misprint with the link to the accompanying Web page for this book. For those readers who would like to experiment with the techniques found in this book or test their own ideas on graph 606 $aData mining 606 $aData structures (Computer science) 606 $aGraphic methods 615 0$aData mining. 615 0$aData structures (Computer science) 615 0$aGraphic methods. 676 $a005.74 701 $aCook$b Diane J.$f1963-$01621465 701 $aHolder$b Lawrence B.$f1964-$01838904 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911020006703321 996 $aMining graph data$94417999 997 $aUNINA