A Collection in Context : Kommentierte Edition der Briefe und Dokumente Sammlung Dr. Karl von Schäffer

• Record Nr.: UNINA9910842274103321
• Autore: Krmnicek Stefan
• Pubbl/distr/stampa: Tübingen, : Tübingen University Press, 2017
• Descrizione fisica: 1 electronic resource (200 p.)
• Soggetti: Classical Greek & Roman archaeology
• Lingua di pubblicazione: Tedesco
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Sommario/riassunto: The first volume of the series Tübinger Numismatische Studien examines the collection of Karl von Schäffer, comprising almost 3000 numismatic objects, which came into the possession of the University of Tübingen as an estate in 1888, in its context of scientific history. The edition of the complete collection documentation is evaluated by contributions to the history of the university collection, a biographical-psychological analysis of the person Karl von Schäffer, studies on the coin trade and on the collecting and research of coins in the 19th century, as well as by a detailed investigation of the networks of the educated bourgeoisie interested in antiquities and coins in the Kingdom of Württemberg. In the context of this dense transmission network, the coins and archival documents not only unfold their significance as important contemporary historical documents for the development of numismatics in the advanced 19th century, but at the same time represent a first-rate source for the reception of ancient coins as significant research objects in art history and cultural history.; Band 1: A Collection in Context Mit der Begründung einer Universitätsmünzsammlung im Jahre 1798 und der Einrichtung der Numismatischen Arbeitsstelle im Jahre 1972 blickt die Universität Tübingen auf eine lange numismatische Tradition zurück. Die neue Reihe „Tübinger Numismatische Studien“ (TNS) soll die Tübinger Numismatik nun ins 21. Jahrhundert führen. Der erste Band der Reihe untersucht die knapp 3000 numismatische Objekte umfassende ; Sammlung Karl von Schäffer, welche als Nachlass im Jahre 1888 in den Besitz der Universität Tübingen gelangte, in ihrem wissenschaftsgeschichtlichen Kontext. Die Edition der vollständigen Sammlungsdokumentation wird durch Beiträge zur universitären Sammlungsgeschichte, einer biographisch-psychologischen Analyse der Person Karl von Schäffer, Studien zum Münzhandel und zum Sammeln und Erforschen von Münzen im 19. Jahrhundert sowie durch eine Detailuntersuchung zu den Netzwerken des antiken- und münzeninteressierten Bildungsbürgertums im Königreich Württemberg ausgewertet. Im Kontext dieses dichten Überlieferungsnetzes entfalten die Münzen und Archivalien nicht nur ihre Bedeutung als wichtige zeitgeschichtliche Dokumente für die Entwicklung der Numismatik im fortgeschrittenen 19. Jahrhundert, sondern stellen zugleich eine Quelle ersten Ranges für die Rezeption von antiken Münzen als kunstgeschichtlich und kulturhistorisch bedeutsame Forschungsobjekte dar.

Advanced Data Mining and Applications : 4th International Conference, ADMA 2008, Chengdu, China, October 8-10, 2008, Proceedings / / edited by Changjie Tang, Charles X. Ling, Xiaofang Zhou, Nick Cercone, Xue Li

• Record Nr.: UNINA9910767543703321
• Pubbl/distr/stampa: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2008
• ISBN: 3-540-88192-1
• Edizione: [1st ed. 2008.]
• Descrizione fisica: 1 online resource (XVII, 759 p.)
• Collana: Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 5139
• Disciplina: 006.312
• Soggetti: Artificial intelligence; Medical sciences; Data mining; Software engineering; Information technology - Management; Application software; Artificial Intelligence; Health Sciences; Data Mining and Knowledge Discovery; Software Engineering; Computer Application in Administrative Data Processing; Computer and Information Systems Applications
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Keynotes -- An Introduction to Transfer Learning -- Autonomy-Oriented Computing (AOC), Self-organized Computability, and Complex Data Mining -- Regular Papers -- Improving Angle Based Mappings -- Mining Natural Language Programming Directives with Class-Oriented Bayesian Networks -- Boosting over Groups and Its Application to Acronym-Expansion Extraction -- A Genetic-Based Feature Construction Method for Data Summarisation -- Suicidal Risk Evaluation Using a Similarity-Based Classifier -- Gene Selection for Cancer Classification Using DCA -- FARS: A Multi-relational Feature and Relation Selection Approach for Efficient Classification -- Enhancing Text Categorization Using Sentence Semantics -- Mining Evolving Web Sessions and Clustering Dynamic Web Documents for Similarity-Aware Web Content Management -- Data Quality in Privacy Preservation for Associative Classification -- Timeline Analysis of Web News Events -- Analysis of Alarm Sequences in a Chemical Plant -- Speed Up SVM Algorithm for Massive Classification Tasks -- Mining Supplemental Frequent Patterns -- A Distributed Privacy-Preserving Association Rules Mining Scheme Using Frequent-Pattern Tree -- Dichotomy Method toward Interactive Testing-Based Fault Localization -- Maintaining the Maximum Normalized Mean and Applications in Data Stream Mining -- Identification of Interface Residues Involved in Protein-Protein Interactions Using Naïve Bayes Classifier -- Negative Generator Border for Effective Pattern Maintenance -- CommTracker: A Core-Based Algorithm of Tracking Community Evolution -- Face Recognition Using Clustering Based Optimal Linear Discriminant Analysis -- A Novel Immune Based Approach for Detection of Windows PE Virus -- Using Genetic Algorithms for Parameter Optimization in Building Predictive Data Mining Models -- Using DataMining Methods to Predict Personally Identifiable Information in Emails -- Iterative Reinforcement Cross-Domain Text Classification -- Extracting Decision Rules from Sigmoid Kernel -- DMGrid: A Data Mining System Based on Grid Computing -- S-SimRank: Combining Content and Link Information to Cluster Papers Effectively and Efficiently -- Open Domain Recommendation: Social Networks and Collaborative Filtering -- An Effective Approach for Identifying Evolving Three-Dimensional Structural Motifs in Protein Folding Data -- Texture Image Retrieval Based on Contourlet Transform and Active Perceptual Similarity Learning -- A Temporal Dominant Relationship Analysis Method -- Leakage-Aware Energy Efficient Scheduling for Fixed-Priority Tasks with Preemption Thresholds -- Short Papers -- Learning and Inferences of the Bayesian Network with Maximum Likelihood Parameters -- TARtool: A Temporal Dataset Generator for Market Basket Analysis -- Dimensionality Reduction for Classification -- Trajectories Mining for Traffic Condition Renewing -- Mining Bug Classifier and Debug Strategy Association Rules for Web-Based Applications -- Test the Overall Significance of p-values by Using Joint Tail Probability of Ordered p-values as Test Statistic -- Mining Interesting Infrequent and Frequent Itemsets Based on MLMS Model -- Text Learning and Hierarchical Feature Selection in Webpage Classification -- The RSO Algorithm for Reducing Number of Set Operations in Association Rule Mining -- Predictive Performance of Clustered Feature-Weighting Case-; Based Reasoning -- Selecting the Right Features for Bipartite-Based Text Clustering -- Image Emotional Classification Based on Color Semantic Description -- A Semi-supervised Clustering Algorithm Based on Must-Link Set -- T-rotation: Multiple Publications of Privacy PreservingData Sequence -- The Integrated Methodology of KPCA and Wavelet Support Vector Machine for Predicting Financial Distress -- Outlier Detection Based on Voronoi Diagram -- AWSum – Data Mining for Insight -- Integrative Neural Network Approach for Protein Interaction Prediction from Heterogeneous Data -- Rules Extraction Based on Data Summarisation Approach Using DARA -- A Rough-Apriori Technique in Mining Linguistic Association Rules -- Mining Causal Knowledge from Diagnostic Knowledge -- Modified Particle Swarm Optimizer with Adaptive Dynamic Weights for Cancer Combinational Chemotherapy -- MPSQAR: Mining Quantitative Association Rules Preserving Semantics -- Using Support Vector Regression for Classification -- Dynamic Growing Self-organizing Neural Network for Clustering -- A Design of Reward Function Based on Knowledge in Multi-agent Learning -- A Learning Method of Detecting Anomalous Pedestrian -- Moment+: Mining Closed Frequent Itemsets over Data Stream -- CDPM: Finding and Evaluating Community Structure in Social Networks -- Using Matrix Model to Find Association Rule Core for Diverse Compound Critiques -- Link-Contexts for Ranking -- DC-Tree: An Algorithm for Skyline Query on Data Streams -- Sequential Pattern Mining for Protein Function Prediction -- Improving Web Search by Categorization, Clustering, and Personalization -- JSNVA: A Java Straight-Line Drawing Framework for Network Visual Analysis -- Recognition of Data Records in Semi-structured Web-Pages Using Ontology and ? 2 Statistical Distribution -- Organizing Structured Deep Web by Clustering Query Interfaces Link Graph -- CBP: A New Efficient Method for Mining Multilevel and Generalized Frequent Itemsets -- Supporting Customer Retention through Real-Time Monitoring of Individual Web Usage -- A Comparative Study of CorrelationMeasurements for Searching Similar Tags -- Structure of Query Modification Process: Branchings -- Mining Top-n Local Outliers in Constrained Spatial Networks -- Mining Concept-Drifting Data Streams with Multiple Semi-Random Decision Trees -- Automatic Web Tagging and Person Tagging Using Language Models -- Real-Time Person Tracking Based on Data Field.
• Sommario/riassunto: This book constitutes the refereed proceedings of the 4th International Conference on Advanced Data Mining and Applications, ADMA 2008, held in Chengdu, China, in October 2008. The 35 revised full papers and 43 revised short papers presented together with the abstract of 2 keynote lectures were carefully reviewed and selected from 304 submissions. The papers focus on advancements in data mining and peculiarities and challenges of real world applications using data mining and feature original research results in data mining, spanning applications, algorithms, software and systems, and different applied disciplines with potential in data mining.