Advanced Data Mining and Applications - Taschenbuch

EAN (ISBN-13): 9783540738701
ISBN (ISBN-10): 3540738703
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2007
Herausgeber: Springer Berlin
634 Seiten
Gewicht: 0,905 kg
Sprache: eng/Englisch

Buch in der Datenbank seit 2007-10-25T10:49:24+02:00 (Zurich)
Detailseite zuletzt geändert am 2023-04-21T09:43:29+02:00 (Zurich)
ISBN/EAN: 9783540738701

ISBN - alternative Schreibweisen:
3-540-73870-3, 978-3-540-73870-1
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: data mining, hong, osm, jian, reda, gao, xue can, osmar, neumann
Titel des Buches: 2007, advanced, lecture notes data mining, harbin, august, international conference computer science, proceedings artificial intelligence conference, off china, china and beyond

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Daten vom Verlag:

Autor/in: Reda Alhajj; Hong Gao; Xue Li; Jianzhong Li; Osmar R. Zaiane
Titel: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Advanced Data Mining and Applications - Third International Conference, ADMA 2007, Harbin, China, August 6-8, 2007 Proceedings
Verlag: Springer; Springer Berlin
636 Seiten
Erscheinungsjahr: 2007-07-17
Berlin; Heidelberg; DE
Sprache: Englisch
106,99 € (DE)
109,99 € (AT)
118,00 CHF (CH)
Available
XVI, 636 p. 201 illus.

BC; Hardcover, Softcover / Informatik, EDV/Informatik; Datenbanken; Verstehen; Informatik; Attribut; Bayesian networks; Business-Intelligence; Fusion; algorithms; bioinformatics; classification; correlation mining; data mining; feature selection; genomics; indexing; intelligence; learning; statistics; Database Management; Artificial Intelligence; Data Mining and Knowledge Discovery; Software Engineering; Computer Application in Administrative Data Processing; Computer and Information Systems Applications; Künstliche Intelligenz; Data Mining; Wissensbasierte Systeme, Expertensysteme; Software Engineering; Computer-Anwendungen in den Sozial- und Verhaltenswissenschaften; Angewandte Informatik; EA

Invited Talk.- Mining Ambiguous Data with Multi-instance Multi-label Representation.- Regular Papers.- DELAY: A Lazy Approach for Mining Frequent Patterns over High Speed Data Streams.- Exploring Content and Linkage Structures for Searching Relevant Web Pages.- CLBCRA-Approach for Combination of Content-Based and Link-Based Ranking in Web Search.- Rough Sets in Hybrid Soft Computing Systems.- Discovering Novel Multistage Attack Strategies.- Privacy Preserving DBSCAN Algorithm for Clustering.- A New Multi-level Algorithm Based on Particle Swarm Optimization for Bisecting Graph.- A Supervised Subspace Learning Algorithm: Supervised Neighborhood Preserving Embedding.- A k-Anonymity Clustering Method for Effective Data Privacy Preservation.- LSSVM with Fuzzy Pre-processing Model Based Aero Engine Data Mining Technology.- A Coding Hierarchy Computing Based Clustering Algorithm.- Mining Both Positive and Negative Association Rules from Frequent and Infrequent Itemsets.- Survey of Improving Naive Bayes for Classification.- Privacy Preserving BIRCH Algorithm for Clustering over Arbitrarily Partitioned Databases.- Unsupervised Outlier Detection in Sensor Networks Using Aggregation Tree.- Separator: Sifting Hierarchical Heavy Hitters Accurately from Data Streams.- Spatial Fuzzy Clustering Using Varying Coefficients.- Collaborative Target Classification for Image Recognition in Wireless Sensor Networks.- Dimensionality Reduction for Mass Spectrometry Data.- The Study of Dynamic Aggregation of Relational Attributes on Relational Data Mining.- Learning Optimal Kernel from Distance Metric in Twin Kernel Embedding for Dimensionality Reduction and Visualization of Fingerprints.- Efficiently Monitoring Nearest Neighbors to a Moving Object.- A Novel Text Classification Approach Based onEnhanced Association Rule.- Applications of the Moving Average of n th -Order Difference Algorithm for Time Series Prediction.- Inference of Gene Regulatory Network by Bayesian Network Using Metropolis-Hastings Algorithm.- A Consensus Recommender for Web Users.- Constructing Classification Rules Based on SVR and Its Derivative Characteristics.- Hiding Sensitive Associative Classification Rule by Data Reduction.- AOG-ags Algorithms and Applications.- A Framework for Titled Document Categorization with Modified Multinomial Naivebayes Classifier.- Prediction of Protein Subcellular Locations by Combining K-Local Hyperplane Distance Nearest Neighbor.- A Similarity Retrieval Method in Brain Image Sequence Database.- A Criterion for Learning the Data-Dependent Kernel for Classification.- Topic Extraction with AGAPE.- Clustering Massive Text Data Streams by Semantic Smoothing Model.- GraSeq: A Novel Approximate Mining Approach of Sequential Patterns over Data Stream.- A Novel Greedy Bayesian Network Structure Learning Algorithm for Limited Data.- Optimum Neural Network Construction Via Linear Programming Minimum Sphere Set Covering.- How Investigative Data Mining Can Help Intelligence Agencies to Discover Dependence of Nodes in Terrorist Networks.- Prediction of Enzyme Class by Using Reactive Motifs Generated from Binding and Catalytic Sites.- Bayesian Network Structure Ensemble Learning.- Fusion of Palmprint and Iris for Personal Authentication.- Enhanced Graph Based Genealogical Record Linkage.- A Fuzzy Comprehensive Clustering Method.- Short Papers.- CACS: A Novel Classification Algorithm Based on Concept Similarity.- Data Mining in Tourism Demand Analysis: A Retrospective Analysis.- Chinese Patent Mining Based on Sememe Statistics and Key-Phrase Extraction.- Classification of Business Travelers Using SVMs Combined with Kernel Principal Component Analysis.- Research on the Traffic Matrix Based on Sampling Model.- A Causal Analysis for the Expenditure Data of Business Travelers.- A Visual and Interactive Data Exploration Method for Large Data Sets and Clustering.- Explorative Data Mining on Stock Data – Experimental Results and Findings.- Graph Structural Mining in Terrorist Networks.- Characterizing Pseudobase and Predicting RNA Secondary Structure with Simple H-Type Pseudoknots Based on Dynamic Programming.- Locally Discriminant Projection with Kernels for Feature Extraction.- A GA-Based Feature Subset Selection and Parameter Optimization of Support Vector Machine for Content – Based Image Retrieval.- E-Stream: Evolution-Based Technique for Stream Clustering.- H-BayesClust: A New Hierarchical Clustering Based on Bayesian Networks.- An Improved AdaBoost Algorithm Based on Adaptive Weight Adjusting.