Advances in Data Mining - Theoretical Aspects and Applications: 7th Industrial Conference, ICDM 2007, Leipzig, Germany, July 14-18, 2007, Proceedings
ICDM / MLDM Medaillie (limited edition) Meissner Porcellan, the White Gold of King August the Strongest of Saxonia ICDM 2007 was the seventh event in the Industrial Conference on Data Mining series and was held in Leipzig (www.data-mining-forum.de). For this edition the Program Committee received 96 submissions from 24 countries (see Fig. 1). After the peer-review process, we accepted 25 high-quality papers for oral presentation that are included in this proceedings book. The topics range from aspects of classification and prediction, clustering, Web mining, data mining in medicine, applications of data mining, time series and frequent pattern mining, and association rule mining. Germany 9,30% 4,17% China 9,30% 1,04% 6,98% 3,13% South Korea Czech Republic 6,98% 3,13% USA 6,98% 2,08% 4,65% 2,08% UK Portugal 4,65% 2,08% Iran 4,65% 2,08% India 4,65% 2,08% Brazil 4,65% 1,04% Hungary 4,65% 1,04% Mexico 4,65% 1,04% Finland 2,33% 1,04% Ireland 2,33% 1,04% Slovenia 2,33% 1,04% France 2,33% 1,04% Israel 2,33% 1,04% Spain 2,33% 1,04% Greece 2,33% 1,04% Italy 2,33% 1,04% Sweden 2,33% 1,04% Netherlands 2,33% 1,04% Malaysia 2,33% 1,04% Turkey 2,33% 1,04% Fig. 1. Distribution of papers among countries Twelve papers were selected for poster presentations that are published in the ICDM Poster Proceedings Volume.
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An Efficient Algorithm for InstanceBased Learning on Data Streams
Softening the Margin in Discrete SVM
A New Method and Comparative Study in the Application of Face Recognition System
Outlier Detection with Streaming Dyadic Decomposition
VISRED Numerical Data Mining with Linear and Nonlinear Techniques
A Case Study
Combining Traditional and NeuralBased Techniques for Ink Feed Control in a Newspaper Printing Press
A Case Study for Detection of Emotions in Speech
Neural Business Control System
A Framework for Discovering and Analyzing Changing Customer Segments
Collaborative Filtering Using Electrical Resistance Network Models
Visual Query and Exploration System for Temporal Relational Database
Towards an Online ImageBased Tree Taxonomy
Clustering by Random Projections
Lightweight Clustering Technique for Distributed Data Mining Applications
Statistical and RuleBased Approach
Improved IR in Cohesion Model for Link Detection System
Improving a StateoftheArt Named Entity Recognition System Using the World Wide Web
A CaseBased Reasoning System to Explain Exceptional Dialysis Patients
The Role of Prototypical Cases in Biomedical CaseBased Reasoning
Distributed Generative Data Mining
PrivacyPreserving Discovery of Frequent Patterns in Time Series
Efficient Non Linear Time Series Prediction Using Non Linear Signal Analysis and Neural Networks in Chaotic Diode Resonator Circuits
Using Disjunctions in Association Mining
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accuracy active learning amount of ink analysis Ant Colony Optimization application approach association rules attributes Case-Based Reasoning classification clustering algorithms Computer concept concept drift corresponding cube data mining data set data streams database defined density dimension dimensional disjunctions distance distributed dyadic tree evaluation examples experiments feature selection function graph Hebbian Learning Heidelberg heuristic ICDM IEEE improved ink key input Instance-Based Learning itemset knowledge label linear link detection system Machine Learning method module Multidimensional Scaling N-gram node novelty detection optimal outliers output parameters patients patterns performance Perner points prediction Principal Component Analysis problem proposed prototypical query expansion random reduce relevant documents represented resistance distance retrieval sample segments solution space Springer statistical step strategy structure subset support vector machines task techniques temporal training data training set tree variables visual query weight
161. lappuse - Topic detection and tracking pilot study: Final report. In Proceedings of the DARPA Broadcast News Transcription and Understanding Workshop, pp.
93. lappuse - PCA is an orthogonal linear transformation that transforms the data to a new coordinate system such that the greatest variance by any projection of the data comes to lie on the first coordinate (called the first principal component), the second greatest variance on the second coordinate, and so on.
99. lappuse - Each neuron is represented by d-dimensional weight vector, m= [m, ..... m<j], where d equals to the dimension of the input vectors. The neurons are connected to adjacent neurons by a neighborhood relation, which dictates the structure of the map. SOM training algorithm updates the best matching unit and its topological neighbors on the map. The region around the best matching unit is pulled towards the presented training sample.
12. lappuse - Recall is the ratio of the number of relevant records retrieved to the total number of relevant records in the database.
48. lappuse - In Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 23-26 2002.
78. lappuse - The organization of the rest of the paper is as follows. In Section 2. we give an overview of the multiprocessor database machine architecture that we have considered.
105. lappuse - References 1. de Oliveira, MCF, Levkowitz, H.: From visual data exploration to visual data mining: A survey. IEEE Trans on Visualization and Computer Graphics 9(3), 378-394 (2003) 2.
105. lappuse - Kramer, MA Nonlinear principal component analysis using autoassociative neural networks.
68. lappuse - GAs operate on a population of potential solutions applying the principle of survival of the fittest to produce (hopefully) better and better approximations to a solution. At each generation, a new set of approximations is created by the process of selecting individuals according to their...