標(biāo)題: Titlebook: Data Mining for Scientific and Engineering Applications; Robert L. Grossman,Chandrika Kamath,Raju R. Nambur Book 2001 Springer Science+Bus [打印本頁] 作者: protocol 時間: 2025-3-21 19:42
書目名稱Data Mining for Scientific and Engineering Applications影響因子(影響力)
書目名稱Data Mining for Scientific and Engineering Applications影響因子(影響力)學(xué)科排名
書目名稱Data Mining for Scientific and Engineering Applications網(wǎng)絡(luò)公開度
書目名稱Data Mining for Scientific and Engineering Applications網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Data Mining for Scientific and Engineering Applications被引頻次
書目名稱Data Mining for Scientific and Engineering Applications被引頻次學(xué)科排名
書目名稱Data Mining for Scientific and Engineering Applications年度引用
書目名稱Data Mining for Scientific and Engineering Applications年度引用學(xué)科排名
書目名稱Data Mining for Scientific and Engineering Applications讀者反饋
書目名稱Data Mining for Scientific and Engineering Applications讀者反饋學(xué)科排名
作者: 逢迎白雪 時間: 2025-3-21 22:06 作者: 點燃 時間: 2025-3-22 04:05 作者: arabesque 時間: 2025-3-22 08:03
Keep Out, or Else: Diary as Body in , and ted and to offer the users a more useful and manageable product. This migration of activities faces several technical and human-factor challenges. As data reduction and mining algorithms are often quite specific to the user’s research needs, the user’s algorithm must be integrated virtually unchange作者: Popcorn 時間: 2025-3-22 11:02 作者: countenance 時間: 2025-3-22 13:26
Graphic Memoirs — autobiografische Comicso much of the work in the traditional data-mining community. We first describe the basic system and follow with a discussion of ongoing work, focusing on efforts in multiscale feature detection and progressive access. Finally, we demonstrate the system for a two-dimensional vector field derived from作者: countenance 時間: 2025-3-22 20:10 作者: 喃喃訴苦 時間: 2025-3-23 00:33
1569-2698 ers who are familiar with the basic principles of data miningand want to learn more about the application of data mining to theirproblem in science or engineering.978-1-4020-0114-7978-1-4615-1733-7Series ISSN 1569-2698 Series E-ISSN 2468-8738 作者: opprobrious 時間: 2025-3-23 04:13 作者: 條街道往前推 時間: 2025-3-23 05:42
Robert L. Grossman,Chandrika Kamath,Raju R. Nambur作者: CHAR 時間: 2025-3-23 12:52 作者: MAUVE 時間: 2025-3-23 13:54
Searching for Bent-Double Galaxies in the First Survey,challenges we face in the application of data mining to a scientific data set. We explain why, in contrast with most commercial data mining applications, data preprocessing requires a considerable effort in scientific applications. Using decision tree classifiers, we describe the work we are doing i作者: Interdict 時間: 2025-3-23 18:15 作者: 聲音刺耳 時間: 2025-3-23 22:24 作者: 協(xié)定 時間: 2025-3-24 04:07
,EVITA — Efficient Visualization and Interrogation of Tera-Scale Data,o much of the work in the traditional data-mining community. We first describe the basic system and follow with a discussion of ongoing work, focusing on efforts in multiscale feature detection and progressive access. Finally, we demonstrate the system for a two-dimensional vector field derived from作者: guzzle 時間: 2025-3-24 09:56
Parallel Algorithms for Clustering High-Dimensional Large-Scale Datasets,to an enormous amount of computation. We have introduced an adaptive grid framework which not only reduces the computation vastly by forming grids based on the data distribution, but also improves the quality of clustering. Clustering algorithms also need to explore clusters in a subspace of the tot作者: 描述 時間: 2025-3-24 12:28
Data Mining for Scientific and Engineering Applications978-1-4615-1733-7Series ISSN 1569-2698 Series E-ISSN 2468-8738 作者: DOSE 時間: 2025-3-24 15:44
Rocío A. Aúz García,Tobias Lotter We briefly describe some of the problems astronomical data and datasets present and give an example from our own efforts to auto- mate the classification of galaxies, and then discuss where “clustering” algorithms may be applicable.作者: Initial 時間: 2025-3-24 21:25
Cyberpunk und Open-Source-Religion bioinformatics and the motivating data management and analysis tasks. Descriptions of successful applications are given, along with an outline of the near-future potential and issues affecting the successful application of data mining.作者: Arroyo 時間: 2025-3-25 02:44
Keep Out, or Else: Diary as Body in , and leation-propagation model of protein folding. We apply a hybrid approach, using a Hidden Markov Model to extract folding initiation sites, and then apply association mining to discover contact potentials. The new hybrid approach achieves accuracy results better than those reported previously.作者: GROG 時間: 2025-3-25 05:25
Emergent Immanent Spiritualities in ,This article describes an internet infrastructure for working with data called DataSpace. A distributed DataSpace application containing data from the 2MASS and DPOSS astronomical data sets is also described. DataSpace is designed so that client applications supporting the remote analysis and distributed mining of data are easy to build.作者: 折磨 時間: 2025-3-25 08:04
A Dataspace Infrastructure for Astronomical Data,This article describes an internet infrastructure for working with data called DataSpace. A distributed DataSpace application containing data from the 2MASS and DPOSS astronomical data sets is also described. DataSpace is designed so that client applications supporting the remote analysis and distributed mining of data are easy to build.作者: 吸引力 時間: 2025-3-25 12:16 作者: 親愛 時間: 2025-3-25 19:48
https://doi.org/10.1007/978-1-4615-1733-7algorithms; bioinformatics; classification; clustering; computer science; data analysis; data mining; datab作者: 到婚嫁年齡 時間: 2025-3-25 20:43
978-1-4020-0114-7Springer Science+Business Media Dordrecht 2001作者: Minutes 時間: 2025-3-26 00:19
: The Scatological Tales of the Fabliaux of data, a brief survey of the work presented at recent conferences in data mining and knowledge discovery might lead one to believe that these techniques are being applied mainly to commercial data sets, to address problems such as customer relationship management, market basket analysis, credit c作者: cardiovascular 時間: 2025-3-26 06:39 作者: 尾巴 時間: 2025-3-26 08:44 作者: 結(jié)果 時間: 2025-3-26 15:46
Michael Hild,Wolfgang L?ngsfeldntinued improvements in acquisition and storage technology are yielding new image sets with data volumes measured in terabytes. Within these large image collections there is a wealth of scientific information, but getting from the data to knowledge is a difficult problem both due to the size of the 作者: 機密 時間: 2025-3-26 17:13 作者: 表示向前 時間: 2025-3-27 00:52
Rocío A. Aúz García,Tobias Lotter this chapter, we describe our experiences in applying data mining to a problem in astronomy, namely, the identification of radio-emitting galaxies with a bent-double morphology. Until recently, astronomers associated with the FIRST (Faint images of the radio Sky at Twenty-cm) survey identified thes作者: padding 時間: 2025-3-27 03:59
Cyberpunk und Open-Source-Religion bioinformatics and the motivating data management and analysis tasks. Descriptions of successful applications are given, along with an outline of the near-future potential and issues affecting the successful application of data mining.作者: maculated 時間: 2025-3-27 06:15
Keep Out, or Else: Diary as Body in , and leation-propagation model of protein folding. We apply a hybrid approach, using a Hidden Markov Model to extract folding initiation sites, and then apply association mining to discover contact potentials. The new hybrid approach achieves accuracy results better than those reported previously.作者: ASSAY 時間: 2025-3-27 10:26 作者: 浪費時間 時間: 2025-3-27 16:27
Introduction: Untaming Comics Memory, a system should help users to locate data sets, to provide preliminary research results quickly and to support data deliveries under users’ request. At George Mason University, we have been developing a data information system with both search and analysis components. In this system, three phases o作者: Boycott 時間: 2025-3-27 21:00
https://doi.org/10.1007/978-3-319-91746-7roduction of this information. This paper reports research undertaken as part of the MODIS effort to map the land cover of North America using the ARTMAP neural network. The main objective is to design a system called ART-VIP (ART for Visualisation and Image Processing) that integrates the ARTMAP ne作者: MIME 時間: 2025-3-28 01:50
https://doi.org/10.1007/978-3-319-91746-7mber of applications. In recent times with the advent of supercomputers and new experimental imaging techniques, terabyte scale data sets are being generated, and hence storage as well as analysis of this data has become a major issue. In this chapter we outline a new approach to tackling these data作者: 方便 時間: 2025-3-28 05:03 作者: 逃避系列單詞 時間: 2025-3-28 09:51
Graphic Memoirs — autobiografische Comicsnt of appropriate data management and visualization techniques has not kept pace with the growth in size and complexity of such datasets. To address these issues, we are developing a prototype, integrated system (EVITA) to facilitate exploration of tera-scale datasets. The cornerstone of the EVITA s作者: Biomarker 時間: 2025-3-28 11:28 作者: MIRTH 時間: 2025-3-28 17:01 作者: 繁榮地區(qū) 時間: 2025-3-28 21:57 作者: Grasping 時間: 2025-3-29 00:32 作者: Melodrama 時間: 2025-3-29 06:40 作者: Veneer 時間: 2025-3-29 09:00 作者: SIT 時間: 2025-3-29 14:54
Mining Residue Contacts in Proteins,leation-propagation model of protein folding. We apply a hybrid approach, using a Hidden Markov Model to extract folding initiation sites, and then apply association mining to discover contact potentials. The new hybrid approach achieves accuracy results better than those reported previously.作者: CRACK 時間: 2025-3-29 15:57
On Mining Scientific Datasets, of data, a brief survey of the work presented at recent conferences in data mining and knowledge discovery might lead one to believe that these techniques are being applied mainly to commercial data sets, to address problems such as customer relationship management, market basket analysis, credit c作者: 閑逛 時間: 2025-3-29 21:00
Understanding High Dimensional and Large Data Sets: Some Mathematical Challenges and Opportunities,nal sets arise naturally in a variety of contexts such as the dynamics of the Internet, imaging for surveillance and diagnostics, and gene sequencing. The significant change in the scale and complexity embodied in these types of data, as well as the intricacies of the underlying phenomena being stud作者: ORBIT 時間: 2025-3-30 00:15
Data Mining at the Interface of Computer Science and Statistics,istical thinking in modern data mining. Data mining has attracted considerable attention both in the research and commercial arenas in recent years, involving the application of a variety of techniques from both computer science and statistics. The chapter discusses how computer scientists and stati作者: 瑣碎 時間: 2025-3-30 04:43
Mining Large Image Collections,ntinued improvements in acquisition and storage technology are yielding new image sets with data volumes measured in terabytes. Within these large image collections there is a wealth of scientific information, but getting from the data to knowledge is a difficult problem both due to the size of the 作者: 夾克怕包裹 時間: 2025-3-30 08:47
Mining Astronomical Databases, We briefly describe some of the problems astronomical data and datasets present and give an example from our own efforts to auto- mate the classification of galaxies, and then discuss where “clustering” algorithms may be applicable.作者: Obituary 時間: 2025-3-30 16:09
Searching for Bent-Double Galaxies in the First Survey, this chapter, we describe our experiences in applying data mining to a problem in astronomy, namely, the identification of radio-emitting galaxies with a bent-double morphology. Until recently, astronomers associated with the FIRST (Faint images of the radio Sky at Twenty-cm) survey identified thes作者: 幼稚 時間: 2025-3-30 17:44
Data Mining Applications in Bioinformatics, bioinformatics and the motivating data management and analysis tasks. Descriptions of successful applications are given, along with an outline of the near-future potential and issues affecting the successful application of data mining.作者: 學(xué)術(shù)討論會 時間: 2025-3-30 23:50
Mining Residue Contacts in Proteins,leation-propagation model of protein folding. We apply a hybrid approach, using a Hidden Markov Model to extract folding initiation sites, and then apply association mining to discover contact potentials. The new hybrid approach achieves accuracy results better than those reported previously.作者: ANTI 時間: 2025-3-31 01:56
KDD Services at the Goddard Earth Sciences Distributed Active Archive Center,te sensing satellites. End users of the data range from instrument scientists to global change and climate researchers to federal agencies and foreign governments. Many of these users apply Knowledge Discovery from Databases (KDD) techniques to large volumes of data (on the order of a terabyte) rece作者: 動物 時間: 2025-3-31 05:05 作者: pacific 時間: 2025-3-31 10:45 作者: 新娘 時間: 2025-3-31 17:14
Real Time Feature Extraction for the Analysis of Turbulent Flows,mber of applications. In recent times with the advent of supercomputers and new experimental imaging techniques, terabyte scale data sets are being generated, and hence storage as well as analysis of this data has become a major issue. In this chapter we outline a new approach to tackling these data作者: ABHOR 時間: 2025-3-31 17:50
Data Mining for Turbulent Flows,p engineers and scientists unravel the causal relationships in the underlying system. In this chapter, we propose several data modeling methods to incorporate spatial and temporal features of scientific simulation data and investigate some of them in the context of developing models for predicting b作者: Interregnum 時間: 2025-3-31 23:08
,EVITA — Efficient Visualization and Interrogation of Tera-Scale Data,nt of appropriate data management and visualization techniques has not kept pace with the growth in size and complexity of such datasets. To address these issues, we are developing a prototype, integrated system (EVITA) to facilitate exploration of tera-scale datasets. The cornerstone of the EVITA s作者: tympanometry 時間: 2025-4-1 04:00 作者: corpuscle 時間: 2025-4-1 09:09 作者: transplantation 時間: 2025-4-1 12:13
,HDDI?: Hierarchical Distributed Dynamic Indexing, global Internet/World Wide Web exemplifies the rapid deployment of such technologies. Despite significant accomplishments in internetworking, however, scalable indexing and data-mining techniques for computational knowledge management lag behind the rapid growth of distributed collections. Hierarch作者: Mumble 時間: 2025-4-1 18:18
Parallel Algorithms for Clustering High-Dimensional Large-Scale Datasets,scientific and commercial applications. Clustering is the process of identifying dense regions in a sparse multi-dimensional data set. Several clustering techniques proposed earlier either lack in scalability to a very large set of dimensions or to a large data set. Many of them require key user inp作者: harangue 時間: 2025-4-1 20:20 作者: 難解 時間: 2025-4-1 23:03
https://doi.org/10.1007/978-3-322-89768-8 networks, graphical models, and flexible predictive modeling. The primary conclusion is that closer integration of computational methods with statistical thinking is likely to become increasingly important in data mining applications.作者: 遭受 時間: 2025-4-2 05:15
Comictheorie(n) und Forschungspositionen introduces HDDI?, focusing on the model building techniques employed at each node of the hierarchy. A novel approach to information clustering based on the contextual transitivity of similarity between terms is introduced. We conclude with several example applications of HDDI? in the textual data mining and information retrieval fields.作者: Picks-Disease 時間: 2025-4-2 09:14
Understanding High Dimensional and Large Data Sets: Some Mathematical Challenges and Opportunities,rge data sets. There is a need, therefore, for new fundamental thinking about these problems and new mathematical approaches. In this paper we review a few such promising directions that draw extensively from fertile areas of harmonic analysis, discrete mathematics, stochastic analysis, and statistical methods.作者: 悲觀 時間: 2025-4-2 13:53
Data Mining at the Interface of Computer Science and Statistics, networks, graphical models, and flexible predictive modeling. The primary conclusion is that closer integration of computational methods with statistical thinking is likely to become increasingly important in data mining applications.作者: ANT 時間: 2025-4-2 19:10
,HDDI?: Hierarchical Distributed Dynamic Indexing, introduces HDDI?, focusing on the model building techniques employed at each node of the hierarchy. A novel approach to information clustering based on the contextual transitivity of similarity between terms is introduced. We conclude with several example applications of HDDI? in the textual data mining and information retrieval fields.作者: Wordlist 時間: 2025-4-2 21:28
