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Author: Publisher: ISBN: Category : Aeronautics Languages : en Pages : 380
Book Description
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Author: Publisher: ISBN: Category : Aeronautics Languages : en Pages : 380
Book Description
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Author: Witold Abramowicz Publisher: Springer ISBN: 3642253709 Category : Business & Economics Languages : en Pages : 322
Book Description
This book constitutes the refereed proceedings of the three workshops that were organized in conjunction with the International Conference on Business Information Systems, BIS 2011, which took place in Poznań, Poland, June 15-17, 2011. The 18 workshop papers presented were carefully reviewed and selected from 38 submissions. The topics covered are applications and economics of knowledge-based technologies (AKTB), business and IT alignment (BITA), and legal information systems (LIT). In addition, eight papers from the co-located Business Process and Services Computing Conference (BPSC) are also included in this volume.
Author: Eric D. Feigelson Publisher: Springer Science & Business Media ISBN: 0387955461 Category : Mathematics Languages : en Pages : 532
Book Description
Digital sky surveys, high-precision astrometry from satellite data, deep-space data from orbiting telescopes, and the like have all increased the quantity and quality of astronomical data by orders of magnitude per year for several years. Making sense of this wealth of data requires sophisticated statistical techniques. Fortunately, statistical methodologies have similarly made great strides in recent years. Powerful synergies thus emerge when astronomers and statisticians join in examining astrostatistical problems and approaches. The book begins with an historical overview and tutorial articles on basic cosmology for statisticians and the principles of Bayesian analysis for astronomers. As in earlier volumes in this series, research contributions discussing topics in one field are joined with commentary from scholars in the other. Thus, for example, an overview of Bayesian methods for Poissonian data is joined by discussions of planning astronomical observations with optimal efficiency and nested models to deal with instrumental effects. The principal theme for the volume is the statistical methods needed to model fundamental characteristics of the early universe on its largest scales.
Author: Weili Wu Publisher: Springer Science & Business Media ISBN: 1461302277 Category : Computers Languages : en Pages : 331
Book Description
Clustering is an important technique for discovering relatively dense sub-regions or sub-spaces of a multi-dimension data distribution. Clus tering has been used in information retrieval for many different purposes, such as query expansion, document grouping, document indexing, and visualization of search results. In this book, we address issues of cluster ing algorithms, evaluation methodologies, applications, and architectures for information retrieval. The first two chapters discuss clustering algorithms. The chapter from Baeza-Yates et al. describes a clustering method for a general metric space which is a common model of data relevant to information retrieval. The chapter by Guha, Rastogi, and Shim presents a survey as well as detailed discussion of two clustering algorithms: CURE and ROCK for numeric data and categorical data respectively. Evaluation methodologies are addressed in the next two chapters. Ertoz et al. demonstrate the use of text retrieval benchmarks, such as TRECS, to evaluate clustering algorithms. He et al. provide objective measures of clustering quality in their chapter. Applications of clustering methods to information retrieval is ad dressed in the next four chapters. Chu et al. and Noel et al. explore feature selection using word stems, phrases, and link associations for document clustering and indexing. Wen et al. and Sung et al. discuss applications of clustering to user queries and data cleansing. Finally, we consider the problem of designing architectures for infor mation retrieval. Crichton, Hughes, and Kelly elaborate on the devel opment of a scientific data system architecture for information retrieval.
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Author: Witold Abramowicz
Author: Eric D. Feigelson
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Author: E. P. Szuszczewicz
Author: Weili Wu