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International Conference on Signals and Electronic Systems, ICSES

作者： Rudolf Kruse Matthias Steinbrecher Christian Moewes Department of Knowledge Processing and Language Engineering Otto-von-Guericke University of Magdeburg Magdeburg Germany

Data analysis has become an integral part in many economic fields. In this paper, we present several real-world applications occurring in the fields of automobile development and manufacturing, finance, and online communities. The given examples share one aspect in common: time. It is not only the fact to find patterns inside data volumes but also to identify them based on their temporal behaviour. We will give examples of dealing with different models of incorporating the temporal aspects. Furthermore some new results in the area of Visual Data Analysis are presented. These methods offer intuitive methods of guiding the user through the process of data and model inspection and assist in drawing conclusions with the help of meaningful graphical representations.

关键词： Sensors Vehicle crash testing Visualization Three dimensional displays Fuzzy sets Companies Association rules

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Information processing and Management of Uncertainty in knowledge-Based Systems

Information Processing and Management of Uncertainty in Know...

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13th International Conference on Information processing and Management of Uncertainty, IPMU 2010

作者： Hüllermeier, Eyke Kruse, Rudolf Hoffmann, Frank Fachbereich Mathematik und Informatik Philipps-Universität Marburg Marburg Germany Department of Knowledge Processing and Language Engineering Otto-von-Guericke University of Magdeburg Universitätsplatz 2 39106 Magdeburg Germany Fakultät für Elektrotechnik und Informationstechnik Technische Universität Dortmund 44221 Dortmund Germany

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An Extended Objective Function for Prototype-less Fuzzy Clustering

An Extended Objective Function for Prototype-less Fuzzy Clus...

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Conference of the North American Fuzzy Information processing Society - NAFIPS

作者： Christian Borgelt Rudolf Kruse European Center for Soft Computing Edificio Cientifico-Tecnológico Mieres Asturias Spain Department of Knowledge Processing and Language Engineering Otto-von-Guericke University of Magdeburg Magdeburg Germany

While in standard fuzzy clustering one optimizes a set of prototypes, one for each cluster, we study fuzzy clustering without prototypes. We define an objective function, which only depends on the distances between data points and the membership degrees of the data points to the clusters, and derive an iterative membership update rule. The properties of the resulting algorithm are then examined, especially w.r.t. to an additional parameter of the objective function (compared to the one proposed in [7]) that can be seen as a more flexible alternative to the fuzzifier. Corresponding experimental results are reported that demonstrate the merits of our approach.

关键词： Prototypes Clustering algorithms Fuzzy sets Shape Partitioning algorithms Design engineering knowledge engineering Iterative algorithms Euclidean distance Covariance matrix

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Finding the Number of Fuzzy Clusters by Resampling

Finding the Number of Fuzzy Clusters by Resampling

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： C. Borgelt R. Kruse Department of Knowledge Processing and Language Engineering Otto-von-Guericke University of Magdeburg Magdeburg Germany

Recently several papers studied resampling approaches to determine the number of clusters in prototype-based clustering. The core idea underlying these approaches is that with the right choice for the number of clusters basically the same cluster structures should be obtained from subsamples of the given data set, while a wrong choice should produce considerably varying cluster structures. In this paper we investigate whether these approaches can be transferred to fuzzy clustering. It turns out that they are applicable to fuzzy clustering as well, but that not all relative cluster evaluation measures that work for crisp clustering can also be used for fuzzy clustering.

关键词： Clustering algorithms Prototypes Design engineering knowledge engineering Gaussian processes Knee Entropy Stability

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Improved Classification of Surface Defects for Quality Control of Car Body Panels

Improved Classification of Surface Defects for Quality Contr...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： C. Doring A. Eichhorn Xiaomeng Wang R. Kruse Department of Knowledge Processing and Language Engineering Faculty of Computer Science University of Magdeburg Magdeburg Germany BMW Group Munich Germany

The detection of the types of local surface form deviations is a major step in the automated quality assessment of car body parts during the manufacturing process. In previous studies we compared the performance of different soft computing techniques for this purpose. We achieved promising results with regard to classification accuracy and interpretability of rule bases, even though the dataset was rather small, high dimensional and unbalanced. In this paper we reconsider the collection of training examples and their assignment to defect types by the quality experts. We attempt to minimize the uncertainty of the quality experts' subjective and error-prone labelling in order to achieve a higher reliability of the defect detection. We show that refined and more accurate classification models can be built on the basis of a preprocessed training set that is more consistent. Using a partially supervised learning strategy we can report improvements in classification accuracy.

关键词： Quality control Manufacturing processes Paints Production Surface treatment Optical distortion Quality assessment Uncertainty Labeling Refining

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knowledge acquisition about the deletion possibility of adnominal verb phrases

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Systems and Computers in Japan 2006年第2期37卷 25-36页

作者： Sakai, Hiroyuki Masuyama, Shigeru Department of Knowledge-Based Information Engineering Toyohashi University of Technology Toyohashi 441-8580 Japan Department of Knowledge-Based Information Engineering Toyohashi University of Technology OR Society of Japan Information Processing Society of Japan Institute of Systems Control and Information Engineers of Japan Association for Natural Language Processing of Japan

We propose a method of acquiring knowledge about the possibility of deletion of adnominal verb phrases from a corpus. Our method acquires such items as the frequency of modification of the noun by adnominal verb phrases and the variety of adnominal verb phrases modifying the noun, from a newspaper corpus, and yields knowledge about the possibility of deletion of adnominal verb phrases by using their statistical information. Our method also identifies adnominal verb phrases modifying nouns with important content as deletable ones. Experimental results show that the precision and the recall attained 77.3% and 69.4%, respectively. © 2006 Wiley Periodicals, Inc.

关键词： knowledge acquisition

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Semantics, Web and Mining: Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2006年 4289 LNAI卷 v-vi页

作者： Berendt, Bettina Hotho, Andreas Mladenič, Dunja Semeraro, Giovanni Spiliopoulou, Myra Stumme, Gerd Van Someren, Maarten Ackermann, Markus Grobelnik, Marko Svátek, Vojtěch Institute of Information Systems Humboldt University Berlin Germany Knowledge and Data Engineering Group University of Kassel Germany J. Stefan Institute Ljubljana Slovenia Department of Informatics University of Bari Italy Faculty of Computer Science Otto-von-Guericke-Univ. Magdeburg Germany Informatics Institute University of Amsterdam Netherlands Dept. of Natural Language Processing Institute for Computer Science University of Leipzig Germany University of Economics Prague Czech Republic

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An implementation of the FP-growth algorithm

An implementation of the FP-growth algorithm

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1st International Workshop on Open Source Data Mining: Frequent Pattern Mining Implementations, OSDM 2005, held in conjunction with the 11th ACM SIGKDD International Conference on knowledge Discovery and Data Mining

作者： Borgelt, Christian Department of Knowledge Processing and Language Engineering School of Computer Science Otto-von-Guericke-University of Magdeburg Universitätsplatz 2 39106 Magdeburg Germany

ISBN: (纸本)1595932100

The FP-growth algorithm is currently one of the fastest approaches to frequent item set mining. In this paper I describe a C implementation of this algorithm, which contains two variants of the core operation of computing a projection of an FP-tree (the fundamental data structure of the FP-growth algorithm). In addition, projected FP-trees are (optionally) pruned by removing items that have become infrequent due to the projection (an approach that has been called FP-Bonsai). I report experimental results comparing this implementation of the FP-growth algorithm with three other frequent item set mining algorithms I implemented (Apriori, Eclat, and Relim). Copyright 2005 ACM.

关键词： Forestry

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Keeping things simple: Finding frequent item sets by recursive elimination

Keeping things simple: Finding frequent item sets by recursi...

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ISBN: (纸本)1595932100

Recursive elimination is an algorithm for finding frequent item sets, which is strongly inspired by the FP-growth algorithm and very similar to the H-mine algorithm. It does its work without prefix trees or any other complicated data structures, processing the transactions directly. Its main strength is not its speed (although it is not slow, even outperforms Apriori and Eclat on some data sets), but the simplicity of its structure. Basically all the work is done in one simple recursive function, which can be written with relatively few lines of code. Copyright 2005 ACM.

关键词： Recursive functions

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Fuzzy frequent pattern discovering based on recursive elimination

Fuzzy frequent pattern discovering based on recursive elimin...

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ICMLA 2005: 4th International Conference on Machine Learning and Applications

作者： Xiaomeng, Wang Borgelt, Christian Kruse, Rudolf Department of Knowledge Processing and Language Engineering School of Computer Science Otto-von-Guericke-University of Magdeburg Universitätsplatz 2 39106 Magdeburg Germany

ISBN: (纸本)0769524958

Real life transaction data often miss some occurrences of items that are actually present. As a consequence some potentially interesting frequent patterns cannot be discovered, since with exact matching the number of supporting transactions may be smaller than the user-specified minimum. In order to allow approximate matching during the mining process, we propose an approach based on transaction editing. Our recursive algorithm relies on a step by step elimination of items from the transaction database together with a recursive processing of transaction subsets. This algorithm works without complicated data structures and allows us to find fuzzy frequent patterns easily. © 2005 IEEE.

关键词： Pattern recognition

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