Advances in Knowledge Discovery and Data Mining : 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001. Proceedings - neues Buch

EAN (ISBN-13): 9783540453574
Erscheinungsjahr: 2001
Herausgeber: Springer Berlin Heidelberg

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ISBN/EAN: 9783540453574

ISBN - alternative Schreibweisen:
978-3-540-45357-4
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: david williams, qing, enno rudolph, william cheung, graham david
Titel des Buches: data mining, knowledge discovery, pacific discovery

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Daten vom Verlag:

Autor/in: David Cheung; Graham J. Williams; Qing Li
Titel: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Advances in Knowledge Discovery and Data Mining - 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001. Proceedings
Verlag: Springer; Springer Berlin
599 Seiten
Erscheinungsjahr: 2003-06-29
Berlin; Heidelberg; DE
Sprache: Englisch
96,29 € (DE)
99,00 € (AT)
118,00 CHF (CH)
Available
XVII, 599 p.

EA; E107; eBook; Nonbooks, PBS / Informatik, EDV/Informatik; Algorithmen und Datenstrukturen; Verstehen; Algorithmic Learning; Bayesian network; Classification; DRM; Data Mining; Database Mining; Information Retrieval; Sequential Learning; Text Summarization; Web Mining; calculus; database; evolutionary algorithm; performance; semantics; C; Data Structures and Information Theory; Artificial Intelligence; Information Storage and Retrieval; IT in Business; Computer and Information Systems Applications; Probability and Statistics in Computer Science; Computer Science; Informationstheorie; Künstliche Intelligenz; Informationsrückgewinnung, Information Retrieval; Data Warehousing; Wirtschaftsmathematik und -informatik, IT-Management; Unternehmensanwendungen; Angewandte Informatik; Mathematik für Informatiker; Wahrscheinlichkeitsrechnung und Statistik; BC

Keynote Presentations.- Incompleteness in Data Mining.- Mining E-Commerce Data: The Good, the Bad, and the Ugly.- Seamless Integration of Data Mining with DBMS and Applications.- Web Mining.- Applying Pattern Mining to Web Information Extraction.- Empirical Study of Recommender Systems Using Linear Classifiers.- iJADE eMiner - A Web-Based Mining Agent Based on Intelligent Java Agent Development Environment (iJADE) on Internet Shopping.- A Characterized Rating Recommend System.- Discovery of Frequent Tree Structured Patterns in Semistructured Web Documents.- Text Mining.- Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification.- Predictive Self-Organizing Networks for Text Categorization.- Meta-learning Models for Automatic Textual Document Categorization.- Efficient Algorithms for Concept Space Construction.- Topic Detection, Tracking, and Trend Analysis Using Self-Organizing Neural Networks.- Automatic Hypertext Construction through a Text Mining Approach by Self-Organizing Maps.- Applications and Tools.- Semantic Expectation-Based Causation Knowledge Extraction: A Study on Hong Kong Stock Movement Analysis.- A Toolbox Approach to Flexible and Efficient Data Mining.- Determining Progression in Glaucoma Using Visual Fields.- Seabreeze Prediction Using Bayesian Networks.- Semi-supervised Learning in Medical Image Database.- On Application of Rough Data Mining Methods to Automatic Construction of Student Models.- Concept Hierarchies.- Concept Approximation in Concept Lattice.- Generating Concept Hierarchies/Networks: Mining Additional Semantics in Relational Data.- Representing Large Concept Hierarchies Using Lattice Data Structure.- Feature Selection.- Feature Selection for Temporal Health Records.- Boosting the Performance of Nearest Neighbour Methods with Feature Selection.- Feature Selection for Meta-learning.- Interestingness.- Efficient Mining of Niches and Set Routines.- Evaluation of Interestingness Measures for Ranking Discovered Knowledge.- Peculiarity Oriented Mining and Its Application for Knowledge Discovery in Amino-Acid Data.- Sequence Mining.- Mining Sequence Patterns from Wind Tunnel Experimental Data for Flight Control.- Scalable Hierarchical Clustering Method for Sequences of Categorical Values.- FFS - An I/O-Efficient Algorithm for Mining Frequent Sequences.- Sequential Index Structure for Content-Based Retrieval.- Spatial and Temporal Mining.- The S 2-Tree: An Index Structure for Subsequence Matching of Spatial Objects.- Temporal Data Mining Using Hidden Markov-Local Polynomial Models.- Patterns Discovery Based on Time-Series Decomposition.- Criteria on Proximity Graphs for Boundary Extraction and Spatial Clustering.- Micro Similarity Queries in Time Series Database.- Association Mining.- Mining Optimal Class Association Rule Set.- Generating Frequent Patterns with the Frequent Pattern List.- User-Defined Association Mining.- Direct and Incremental Computing of Maximal Covering Rules.- Towards Efficient Data Re-mining (DRM).- Data Allocation Algorithm for Parallel Association Rule Discovery.- Classification and Rule Induction.- Direct Domain Knowledge Inclusion in the PA3 Rule Induction Algorithm.- Hierarchical Classification of Documents with Error Control.- An Efficient Data Compression Approach to the Classification Task.- Combining the Strength of Pattern Frequency and Distance for Classification.- A Scalable Algorithm for Rule Post-pruning of Large Decision Trees.- Optimizing the Induction of Alternating Decision Trees.- Building Behaviour Knowledge Space to Make Classification Decision.- Clustering.- Efficient Hierarchical Clustering Algorithms Using Partially Overlapping Partitions.- A Rough Set-Based Clustering Method with Modification of Equivalence Relations.- Importance of Individual Variables in the k-Means Algorithm.- A Hybrid Approach to Clustering in Very Large Databases.- Advanced Topics and New Methods.- A Similarity Indexing Method for the Data Warehousing - Bit-Wise Indexing Method.- Rule Reduction over Numerical Attributes in Decision Trees Using Multilayer Perceptron.- Knowledge Acquisition from Both Human Expert and Data.- Neighborhood Dependencies for Prediction.- Learning Bayesian Networks with Hidden Variables Using the Combination of EM and Evolutionary Algorithms.- Interactive Construction of Decision Trees.- An Improved Learning Algorithm for Augmented Naive Bayes.- Generalised RBF Networks Trained Using an IBL Algorithm for Mining Symbolic Data.
Includes supplementary material: sn.pub/extras