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- ArticleOctober 2007
Classification with Choquet Integral with Respect to Signed Non-additive Measure
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 283–288In order to better understand the nature of classification, a data modeling-based perspective is needed. When the attributes in the database have high interactions that make the non-linear relationships, the use of linear model as the aggregation tool ...
- ArticleOctober 2007
Privacy-Preserving k-NN for Small and Large Data Sets
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 699–704It is not surprising that there is strong interest in k- NN queries to enable clustering, classification and outlier- detection tasks. However, previous approaches to privacy- preserving k-NN are costly and can only be realistically ap- plied to small ...
- ArticleOctober 2007
Characterizing RNA Secondary-Structure Features and Their Effects on Splice-Site Prediction
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 89–94composition and by their three-dimensional shape, called the secondary structure. The secondary structure of a pre-mRNA sequence may have a strong influence on gene splicing. In our previous work, we showed that a splice-site model employing sequence ...
- ArticleOctober 2007
A Comparative Study of Methods for Transductive Transfer Learning
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 77–82The problem of transfer learning, where information gained in one learning task is used to improve performance in another related task, is an important new area of re- search. While previous work has studied the supervised ver- sion of this problem, we ...
- ArticleOctober 2007
Spatial Clustering Using the Likelihood Function
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 637–642Clustering has been widely used as a tool to group multivariate observations that have similar characteristics. However, there have been few attempts at formulating a method to group similar multivariate observations while taking into account their ...
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- ArticleOctober 2007
Segmenting Multi-attribute Sequences Using Dynamic Bayesian Networks
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 465–470Discovering dependencies between attributes in multi- attribute event sequences (multi-sequences), also known as synchronized multi-stream sequences, is an important prob- lem in many domains, including monitoring systems and molecular biology. Many ...
- ArticleOctober 2007
Space-Time Summarization of Multisensor Time Series. Case of Missing Data
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 631–636https://doi.org/10.1109/ICDMW.2007.99A wide variety of application domains have to deal with incomplete data sets. In particular, data from sensors net- works are often incomplete due to factors like partial sys- tem failures or bad conditions of measurements. With such incomplete massive ...
- ArticleOctober 2007
Skewed Class Distributions and Mislabeled Examples
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 477–482https://doi.org/10.1109/ICDMW.2007.96Both imbalanced data and class noise are problems which have received attention in data mining research, how- ever learning from imbalanced data with labeling errors has not been adequately addressed. We present system- atic experimentation on ...
- ArticleOctober 2007
Simultaneous Heterogeneous Data Clustering Based on Higher Order Relationships
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 387–392https://doi.org/10.1109/ICDMW.2007.94Co-clustering on heterogeneous data has attracted more and more attention in web mining and information retrieval. The clustering approaches for two type heterogeneous data (bi-type co-clustering) have been well studied in the lit- erature. However, the ...
- ArticleOctober 2007
A Regularized Multiple Criteria Linear Program for Classification
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 253–258https://doi.org/10.1109/ICDMW.2007.9Although multiple criteria mathematical programs (MCMP), as alternative methods of classification, have been used in various real-life data mining problems, its mathematical structure of solvability are still challenge- able. This paper proposes a ...
- ArticleOctober 2007
Semi-supervised Kernel Logistic Regression and Its Extension to Active Learning Based on A-Optimality
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 277–282https://doi.org/10.1109/ICDMW.2007.88The purpose of this paper is to introduce new approaches for kernel logistic regression (KLR) in a semi-supervised setting. Using the special structure of Laplacian kernel matrices, we propose new formulations which minimize the negative log likelihood ...
- ArticleOctober 2007
Semi-supervised Clustering Using Bayesian Regularization
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 361–366https://doi.org/10.1109/ICDMW.2007.87Text clustering is most commonly treated as a fully au- tomated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwise (must-link and cannot-link) constraints. This paper introduces a ...
- ArticleOctober 2007
Semi-Automatic Semantic Annotation of Images
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 45–50https://doi.org/10.1109/ICDMW.2007.86Detailed, consistent semantic annotation of large collections of multimedia data is difficult and time- consuming. In domains such as eScience, digital curation and industrial monitoring, fine-grained high- quality labeling of regions enables advanced ...
- ArticleOctober 2007
Robust Unsupervised and Semisupervised Bounded C-Support Vector Machines
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 331–336https://doi.org/10.1109/ICDMW.2007.83Support Vector Machines (SVMs) have been dominant learning techniques for almost ten years, and mostly ap- plied to supervised learning problems. Recently two-class unsupervised and semi-supervised classification algorithms based on Bounded C-SVMs, ...
- ArticleOctober 2007
Reducing UK-Means to K-Means
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 483–488https://doi.org/10.1109/ICDMW.2007.81This paper proposes an optimisation to the UK-means algorithm, which generalises the k-means algorithm to han- dle objects whose locations are uncertain. The location of each object is described by a probability density function (pdf). The UK-means ...
- ArticleOctober 2007
Query Expansion Using Topic and Location
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 619–624https://doi.org/10.1109/ICDMW.2007.80Users use a few keywords to post queries to search engines. Search engines, often, fail to return answers that their users seek because the keyword queries incompletely specify the information being sought and because of the ambiguity of natural ...
- ArticleOctober 2007
A Novel Rule Weighting Approach in Classification Association Rule Mining
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 271–276https://doi.org/10.1109/ICDMW.2007.8Classification Association Rule Mining (CARM) is a recent Classification Rule Mining approach that builds an Association Rule Mining based classifier using Classification Association Rules (CARs). Regardless of which particular CARM algorithm is used, a ...
- ArticleOctober 2007
Predicting and Optimizing Classifier Utility with the Power Law
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 219–224https://doi.org/10.1109/ICDMW.2007.73When data collection is costly and/or takes a significant amount of time, an early prediction of the classifier performance is extremely important for the design of the data mining process. Power law has been shown in the past to be a good predictor of ...
- ArticleOctober 2007
Pattern Mining as Abduction: From Snapshots to Spatio-Temporal Sequential Patterns
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 613–618https://doi.org/10.1109/ICDMW.2007.71The focus of this paper is towards development of a logical framework for mining spatio-temporal sequential patterns. The spatial representation language RCC-8, of- ten referred to as Region Connection Calculus and its spatio-temporal extension, ST0, a ...
- ArticleOctober 2007
On Regional Association Rule Scoping
ICDMW '07: Proceedings of the Seventh IEEE International Conference on Data Mining WorkshopsPages 595–600https://doi.org/10.1109/ICDMW.2007.68A special challenge for spatial data mining is that information is not distributed uniformly in spatial data sets. Consequently, the discovery of regional knowledge is of fundamental importance. Unfortunately, regional patterns frequently fail to be ...