Advanced Data Mining and Applications
Third International Conference, ADMA 2007 Harbin, China, August 6-8, 2007. Proceedings
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English
Data Mining and Knowledge Discovery
Information Systems Applications (incl. Internet)
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Article
Vocabulary Use in XML Standards in the Financial Market Domain
Vocabulary issues are central to XML-based e-commerce standards. The rapid increase in the number of XML standards has made the vocabulary issues a critical area of XML applications. This paper reports the res...
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Article
Mining Condensed Frequent-Pattern Bases
Frequent-pattern mining has been studied extensively and has many useful applications. However, frequent-pattern mining often generates too many patterns to be truly efficient or effective. In many application...
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Chapter and Conference Paper
Planning with Domain Rules Based on State-Independent Activation Sets
In AI planning community, planning domains with derived predicates are very challenging to many planning system. Derived predicate is a new application of domain rules and domain knowledge acquisition. In this...
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Chapter and Conference Paper
Extracting Minimum Unsatisfiable Cores with a Greedy Genetic Algorithm
Explaining the causes of infeasibility of Boolean formulas has practical applications in various fields. We are generally interested in a minimum explanation of infeasibility that excludes irrelevant informati...
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Article
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its application to transaction or ...
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Chapter and Conference Paper
Hybrid O( \(n \sqrt{n}\) ) Clustering for Sequential Web Usage Mining
We propose a natural neighbor inspired O( \(n \sqrt{n}\) ) hybrid clustering algorithm that combines medoid-based partiti...
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Chapter and Conference Paper
Training Classifiers for Unbalanced Distribution and Cost-Sensitive Domains with ROC Analysis
ROC (Receiver Operating Characteristic) has been used as a tool for the analysis and evaluation of two-class classifiers, even the training data embraces unbalanced class distribution and cost-sensitiveness. H...
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Chapter and Conference Paper
Clustering Massive Text Data Streams by Semantic Smoothing Model
Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organization and topic detection and tracing e...
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Chapter and Conference Paper
Pattern Recognition in Stock Data Based on a New Segmentation Algorithm
In trying to find the features and patterns within the stock time series, time series segmentation is often required as one of the fundamental components in stock data mining. In this paper, a new stock time s...
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Chapter and Conference Paper
Recognition of JPEG Compressed Face Images Based on AdaBoost
This paper presents an advanced face recognition system based on AdaBoost algorithm in the JPEG compressed domain. First, the dimensionality is reduced by truncating some of the block-based DCT coefficients an...
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Chapter and Conference Paper
PPN 2007 PC Co-chairs’ Message
Welcome to the proceedings of the 1st International Workshop on Peer-to-Peer Networks (PPN 2007). The workshop was held in conjunction with the On The Move Federated Conference and Workshops (OTM2007), Novembe...
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Chapter and Conference Paper
Spectral Edit Distance Method for Image Clustering
The spectral graph theories have been widely used in the domain of image clustering where editing distances between graphs are critical. This paper presents a method for spectral edit distance between the grap...
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Chapter and Conference Paper
An Improved AdaBoost Algorithm Based on Adaptive Weight Adjusting
The base classifier, which is trained by AdaBoost ensemble learning algorithm, has a constant weight for all test instances. From the view of iterative process of AdaBoost, every base classifier has good class...
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Chapter and Conference Paper
Camera Motion Analysis Towards Semantic-Based Video Retrieval in Compressed Domain
To reduce the semantic gap between low-level visual features and the richness of human semantics, this paper proposes new algorithms, by virtue of the combined camera motion descriptors with multi-threshold, t...
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Book and Conference Proceedings
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Article
Capabilities of outlier detection schemes in large datasets, framework and methodologies
Outlier detection is concerned with discovering exceptional behaviors of objects. Its theoretical principle and practical implementation lay a foundation for some important applications such as credit card fra...
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Chapter and Conference Paper
Reduction Based Symbolic Value Partition
Theory of Rough Sets provides good foundations for the attribute reduction processes in data mining. For numeric attributes, it is enriched with appropriately designed discretization methods. However, not much...
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Chapter and Conference Paper
(α, k)-anonymity Based Privacy Preservation by Lossy Join
Privacy-preserving data publication for data mining is to protect sensitive information of individuals in published data while the distortion to the data is minimized. Recently, it is shown that (α,k)-anonymity i...
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Chapter and Conference Paper
Mining Invisible Tasks from Event Logs
Most existing process mining algorithms have problems in dealing with invisible tasks. In this paper, a new process mining algorithm named α # is proposed, which extends the mining capacity of the...
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Chapter and Conference Paper
Transforming the Adaptive Irregular Out-of-Core Applications for Hiding Communication and Disk I/O
In adaptive irregular out-of-core applications, communications and mass disk I/O operations occupy a large portion of the overall execution. This paper presents a program transformation scheme to enable overla...
