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Joint International Conference on Advances in data and Web Management, APWeb/WaiM 2009

作者： Xiao, Yanqin Zhang, Yansong Wang, Shan Chen, Hong Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China MOE Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Computer Center Hebei University Baoding Hebei 071002 China Department of Computer Science Harbin Finance College Harbin 150030 China

ISBN: (纸本)9783642006715

What-if analysis is an important method to analyze the hypothetical scenarios based on the historical data. It provides useful information for the decision- maker. Multiple versions are critical to what-if analysis. In this paper, we analyze the problem of multiple versions data processing and the incremental computation of cubes in what-if analysis, proposing a strategy to process multiple versions of what-if data. Our solution can adopt different data processing methods according to the type of aggregate functions, the efficiency of multiple versions data processing is improved. Furthermore, we proposes an algorithm of incremental computation of CUBE for max(min) function to reduce the access time of fact table, and the experimental results showed that the performance is improved about 10%. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Decision making

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The tradeoff of delta table merging and re-writing algorithms in what-if analysis application

The tradeoff of delta table merging and re-writing algorithm...

引用

Joint International Conference on Advances in data and Web Management, APWeb/WaiM 2009

作者： Zhang, Yansong Zhang, Yu Xiao, Yanqin Wang, Shan Chen, Hong Key Laboratory of the Ministry of Education for Data Engineering and Knowledge Engineering Renmin University of China Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Department of Computer Science Harbin Finance College Harbin 150030 China Computer Center Hebei University Baoding Hebei 071002 China

ISBN: (纸本)9783642006715

What-if analysis can provide more meaningful information than classical OLAP. Multi-scenario hypothesis based on historical data needs efficient what-if data view support. In general, delta table for what-if analysis is more general than other solutions such as query re-writing prototype of Sesame. Delta table is independent of base table and is more suitable to represent complex hypothetical updates and multi-version hypothetical updates. Due to low efficiency of traditional delta table merging algorithm which is based on set operation, there are few researches focus on delta table merging algorithm but on query re-writing algorithm. By analyzing the difference between what-if query and what-if analysis and improving the delta table merging algorithm, we propose novel algorithms without set operation of difference. Considering the feature of aggregate operations in OLAP analysis, pre-merge algorithm is presented without the generation of what if data view before group-bys in the scenario of SUM, AVERAGE and COUNT function OLAP queries. In our experiments, the pre-merge algorithm greatly improved the efficiency of delta table merging procedure which is close to base group-by statement and superior to the re-writing algorithm. A complete comparison between all candidate delta table merging algorithms and re-writing algorithm with different what-if update conditions of update, deletion, insertion and mixed what-if updates is exhibited in our experiments, the policy of what-if analysis among different types is also discussed. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Merging

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Personal Financial Market Segmentation Based on Clustering Ensembles

Personal Financial Market Segmentation Based on Clustering E...

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computer science and Information engineering, CSIE, WRI World Congress on FLAGGED

作者： Guoxun Wang Guangli Nie Peng Zhang Yong Shi School of Computer Science and Information Engineering Henan University China Research Center on Fictitious Economy abd Data Science Chinese Academy and Sciences Beijing China

Market segmentation is one of the most important areas of knowledge-based marketing. When it comes to personal financial services in retail banks, it is really a challenging task as data bases are large and multidimensional. The conventional ways in customer segmentation are knowledge based and often get bias results. On the contrary, data mining can deal with mass of data and never overlook any important phenomena. In this paper, we choose the clustering ensemble method to do customer segmentation due to labeled data sets are not available. Through the experiments and tests in the real personal financial business, we can make a conclusion that our models reflect the true characteristics of various types of customers and can be used to find the investment orientations of customers.

关键词： computer science

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Mining association rules among gene functions in clusters of similar gene expression maps

Mining association rules among gene functions in clusters of...

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IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

作者： Li An Zoran Obradovic Desmond Smith Olivier Bodenreider Vasileios Megalooikonomou Data Engineering Laboratory Department of Computer and Information Sciences Temple University PA USA Center of Information Science and Technology Temple University PA USA Department of Molecular and Medical Pharmacology David Geffen School of Medicine UCLA CA USA Lister Hill National Center of Biomedical Communications U.S. National Library of Medicine Washington D.C. DC USA

Association rules mining methods have been recently applied to gene expression data analysis to reveal relationships between genes and different conditions and features. However, not much effort has focused on detecting the relation between gene expression maps and related gene functions. Here we describe such an approach to mine association rules among gene functions in clusters of similar gene expression maps on mouse brain. The experimental results show that the detected association rules make sense biologically. By inspecting the obtained clusters and the genes having the gene functions of frequent itemsets, interesting clues were discovered that provide valuable insight to biological scientists. Moreover, discovered association rules can be potentially used to predict gene functions based on similarity of gene expression maps.

关键词： data mining Association rules Gene expression Mice Genomics Bioinformatics data analysis Proteins data engineering Laboratories

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Prediction of protein sub-cellular localization using information from texts and sequences

Prediction of protein sub-cellular localization using inform...

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2008 Current Trends in Biomedical Natural Language Processing, BioNLP 2008

作者： Chun, Hong-Woo Yamasaki, Chisato Saichi, Naomi Tanaka, Masayuki Hishiki, Teruyoshi Imanishi, Tadashi Gojobori, Takashi Kim, Jin-Dong Tsujii, Jun'Ichi Takagi, Toshihisa Database Center for Life Science Research Organization of Information and System University of Tokyo Engineering 12th Bldg. 2-11-16 Yayoi Bunkyo-ku Tokyo113-0032 Japan Japan Biological Information Research Center Japan Biological Informatics Consortium Japan Biological Information Research Center National Institute of Advanced Industrial Science and Technology Japan Department of Computer Science University of Tokyo Japan Graduate School of Information Science and Technology Hokkaido University Japan Center for Information Biology DNA Data Bank of Japan National Institute of Genetics United Kingdom School of Informatics University of Manchester United Kingdom National Centre for Text Mining United Kingdom Department of Computational Biology University of Tokyo Japan

ISBN: (纸本)9781932432114

关键词： Proteins

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Select Objective Functions for Multiple Criteria Programming Classification

Select Objective Functions for Multiple Criteria Programming...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Peng Zhang Yingjie Tian Zhiwang Zhang aihua Li Xingquan Zhu Chinese Academy of Sciences Beijing China Reasearch Center on Fictitous Economy & Data Science Chinese Academy and Sciences Beijing China School of Manag Science & Engineering Central University of Finance and Economics Beijing China Department of Computer Science & Engineering Florida Atlantic University Boca Raton FL USA

Existing supervised learning models are generally built upon the basis of only one single objective function, through the minimizing of the square-loss (neural networks) or the minimizing of the information entropy (decision tree). Due to the inherent complexity of the real-life data, learning models merely based on only one single objective function are always inadequate. Consequently, many well-known classification models adopt multiple objective optimization to guide the learning process. For example, Fisherpsilas linear discriminant analysis (LDA) is built by maximizing the ldquobetween-class variancerdquo (the first objective function) and minimizing the ldquowithin-class variancerdquo (the second objective function); SVM is built by maximizing the ldquomarginal distancerdquo (the first objective function) and minimizing the ldquoerror distancerdquo (the second objective function). In this paper, we combine Fisherpsilas LDA (maximizing the ldquobetween-class variancerdquo) measure and SVMpsilas minimizing the ldquoerror distancerdquo measure to formulate a new multiple objective classification model, namely minimal error and maximal between-class variance (MEMBV) model. Experimental results demonstrate the performance of the proposed new model on synthetic and real-life datasets.

关键词： Functional programming Linear discriminant analysis Support vector machines Support vector machine classification data mining Intelligent agent Neural networks Information entropy Decision trees Error correction

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Epileptic seizure detection

Epileptic seizure detection

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作者： Schuyler, Ronald White, Andrew Staley, Kevin Cios, Krzysztof J. Computational Bioscience Ph.D. Program UCDHSC United States University of Colorado United States American Epilepsy Society Society for Neuroscience United States Department of Neurology Massachusetts General Hospital Harvard Medical School United States Staley Lab. United States University of Colorado at Denver Health Sciences Center United States University of Colorado Bioenergetics Institute United States Data Mining and Bioinformatics Laboratory Turkey Polish Academy of Arts and Sciences Poland Dept. of Computer Science and Engineering University of Colorado at Denver Health Sciences Center P.O. Box 173364 Denver CO 80217-3364 United States

No abstract available

关键词：

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Noise characteristics of 340 nm and 280 nm GaN-based light emitting diodes

Noise characteristics of 340 nm and 280 nm GaN-based light e...

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作者： Sawyer, Shayla Rumyantsev, Sergey L. Pala, Nezih Shur, Michael S. Bilenko, Yuriy Gaska, Remis Kosterin, Pavel V. Salzberg, Brian M. Department of Electrical Computer and Systems Engineering Center for Broadband Data Transport Science and Technology CII 9017 Rensselaer Polytechnic Institute Troy NY 12180-3590 United States Sensor Electronic Technology Inc. 1195 Atlas Road Columbia SC 29209 United States Departments of Neuroscience and Physiology University of Pennsylvania School of Medicine Philadelphia PA 19104 United States

Low frequency fluctuations in light intensity of 340 nm and 280 nm GaN-based light emitting diodes (LEDs) are compared with noise properties of other commercially available UV and visible wavelength LEDs and halogen lamps. At low frequencies, LEDs can exhibit lower levels of noise than halogen lamps. An LED noise quality factor β is estimated for the UV LEDs. © World Scientific Publishing Company.

关键词： Light emitting diodes

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NOISE CHARACTERISTICS OF 340 nm AND 280 nmGaN-BASED LIGHT EMITTING DIODES

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International Journal of High Speed Electronics and Systems 2004年第3期14卷 702-707页

作者： SHAYLA SAWYER SERGEY L. RUMYANTSEV NEZIH PALA MICHAEL S. SHUR YURIY BILENKO REMIS GASKA PAVEL V. KOSTERIN BRIAN M. SALZBERG Department of Electrical Computer and Systems Engineering Center for Broadband Data Transport Science and Technology CII 9017 Rensselaer Polytechnic Institute Troy NY 12180-3590 USA Sensor Electronic Technology Inc. 1195 Atlas Road Columbia SC 29209 USA Departments of Neuroscience and Physiology University of Pennsylvania School of Medicine Philadelphia PA 19104 USA

Low frequency fluctuations in light intensity of 340 nm and 280 nm GaN -based light emitting diodes (LEDs) are compared with noise properties of other commercially available UV and visible wavelength LEDs and halogen lamps. At low frequencies, LEDs can exhibit lower levels of noise than halogen lamps. An LED noise quality factor β is estimated for the UV LEDs.

关键词：

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Noise characteristics of 340 nm and 280 in GaN-based light emitting diodes

Noise characteristics of 340 nm and 280 in GaN-based light e...

引用

IEEE Conference on High Performance Devices

作者： S. Sawyer S.L. Rumyantsev N. Pala M.S. Shur Y. Bilenko R. Gaska P.V. Kosterin B.M. Salzberg Department of Electrical Computer and Systems Engineering Center for Broadband Data Transport Science and Technology Cll 9017 Rensselaer Polytechnic Institute Troy NY USA Sensor Electronic Technology Inc.orporated Columbia SC USA Departments of Neuroscience and Physiology University of Pennsylvania School of Medicine Philadelphia PA USA

关键词： Light emitting diodes Optical noise Fluctuations Low-frequency noise Light sources Frequency Photodiodes Resistors Proteins Batteries

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