Grouping Multidimensional Data

Grouping Multidimensional Data

The level of detail, the breadth of coverage, and the comprehensive bibliography make this book a perfect fit for researchers and graduate students in data mining and in many other important related application areas.

Author: Jacob Kogan

Publisher: Springer Science & Business Media

ISBN: 9783540283492

Category: Computers

Page: 268

View: 611

Clustering is one of the most fundamental and essential data analysis techniques. Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection. Kogan and his co-editors have put together recent advances in clustering large and high-dimension data. Their volume addresses new topics and methods which are central to modern data analysis, with particular emphasis on linear algebra tools, opimization methods and statistical techniques. The contributions, written by leading researchers from both academia and industry, cover theoretical basics as well as application and evaluation of algorithms, and thus provide an excellent state-of-the-art overview. The level of detail, the breadth of coverage, and the comprehensive bibliography make this book a perfect fit for researchers and graduate students in data mining and in many other important related application areas.
Categories: Computers

A Likelihood Based Grouping Method for Multidimensional Observations

A Likelihood Based Grouping Method for Multidimensional Observations

SYNOPSIS This paper discusses a method for data clustering. The technique
results in homogeneous subordinate data populations. Inherent to this method is
the use of Fisher's likelihood theory to define the distances between groups of
data.

Author: Rudi Hamerslag

Publisher:

ISBN: UCBK:C101316682

Category: Automobile driving

Page: 36

View: 428

Categories: Automobile driving

Data Warehousing and Knowledge Discovery

Data Warehousing and Knowledge Discovery

Notice we are considering the “group by” and “aggregation” as relational
operators, and both will be justified consequently below. Since multidimensional
tables contain (1) identifier fields (i.e. identifier Descriptors) identifying data, for
instance: ...

Author: Il Yeol Song

Publisher: Springer Science & Business Media

ISBN: 9783540745532

Category: Computers

Page: 484

View: 267

This book constitutes the refereed proceedings of the 8th International Conference on Data Warehousing and Knowledge Discovery, DaWak 2007, held in Regensburg, Germany, September 2007. Coverage includes ETL processing, multidimensional design, OLAP and multidimensional model, cubes processing, data warehouse applications, frequent itemsets, ontology-based mining, clustering, association rules, miscellaneous applications, and classification.
Categories: Computers

Multidimensional Poverty among Social Groups in Kerala

Multidimensional Poverty among Social Groups in Kerala

Table: 6.13 RHDEI and MPI of Social Groups Multidimensional Poverty Index (
MPI) Block Panchayaths RHDEI SC ST ... 65.5 Source: Estimation of the
Investigator based on primary data There is no significant difference existing
among the ...

Author: Shibu Sivaraman K.C. Baiju

Publisher: Cambridge Scholars Publishing

ISBN: 9781527515000

Category: Health & Fitness

Page: 135

View: 593

This book narrates the living conditions and incidence of poverty among households belonging to the different social groups in Kerala, India. Using a micro-level study, it investigates the inter-group variations with regards to the incidence of multidimensional poverty in the sample area, the Kasaragod District, Kerala. The Regional Human Development Enabling Index (RHDEI) and the Multidimensional Poverty Index (MPI) are the main tools used for analysis here. The book highlights the incidence, intensity, and disparity of multidimensional poverty in Kerala, and clearly pinpoints the intra-state mirage of the achievements of Kerala in the dimensions of human development among the social groups living in the state. The book also explores the socio-cultural barriers of these marginalized groups, which should become the focus and concern for policy makers and stakeholders in governance.
Categories: Health & Fitness

Finding Groups in Data

Finding Groups in Data

191 Error sum dissimilarity coefficient, 308 Error sum of squares, 112, 231, 243,
277 one-dimensional data. ... 164-165 treating ratio-scaled variables as, 31
ISODATA, 115 multidimensional data, 116 Iterative procedure, 155, 171, 254,273
 ...

Author: Leonard Kaufman

Publisher: John Wiley & Sons

ISBN: 9780470317488

Category: Mathematics

Page: 342

View: 654

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Cluster analysis is the increasingly important and practical subject of finding groupings in data. The authors set out to write a book for the user who does not necessarily have an extensive background in mathematics. They succeed very well." —Mathematical Reviews "Finding Groups in Data [is] a clear, readable, and interesting presentation of a small number of clustering methods. In addition, the book introduced some interesting innovations of applied value to clustering literature." —Journal of Classification "This is a very good, easy-to-read, and practical book. It has many nice features and is highly recommended for students and practitioners in various fields of study." —Technometrics An introduction to the practical application of cluster analysis, this text presents a selection of methods that together can deal with most applications. These methods are chosen for their robustness, consistency, and general applicability. This book discusses various types of data, including interval-scaled and binary variables as well as similarity data, and explains how these can be transformed prior to clustering.
Categories: Mathematics

Advanced Data Mining and Applications

Advanced Data Mining and Applications

1 Introduction Clustering is a process of grouping multidimensional input data
spaces into multiple sets of similar objects, which makes the objects in the same
cluster have higher similarity than those in others. Due to its unsupervised
learning ...

Author: Xue Li

Publisher: Springer Science & Business Media

ISBN: 9783540370253

Category: Computers

Page: 1114

View: 371

Here are the proceedings of the 2nd International Conference on Advanced Data Mining and Applications, ADMA 2006, held in Xi'an, China, August 2006. The book presents 41 revised full papers and 74 revised short papers together with 4 invited papers. The papers are organized in topical sections on association rules, classification, clustering, novel algorithms, multimedia mining, sequential data mining and time series mining, web mining, biomedical mining, advanced applications, and more.
Categories: Computers

1963 Census of Transportation Commodity transportation survey pts 1 2 Commodity groups pts 3 4 Shipper groups and production areas

1963 Census of Transportation  Commodity transportation survey  pts  1 2  Commodity groups  pts  3 4  Shipper groups and production areas

The 3 - digit classes are used to present multidimensional data and to better
define traffic patterns . In total , 53 groups of 3 - digit commodities cover . ing 55
commodities were tabulated in seven tables showing information on tons and ton
 ...

Author: United States. Bureau of the Census

Publisher:

ISBN: UOM:39015021089258

Category: Transportation

Page:

View: 828

Categories: Transportation

Encyclopedia of Data Warehousing and Mining

Encyclopedia of Data Warehousing and Mining

Multidimensional data are obtained by applying aggregations and statistical
functions to elementary data, or more precisely to data groups, each containing a
subset of the data and homogeneous with respect to a given set of attributes.

Author: Wang, John

Publisher: IGI Global

ISBN: 9781591405597

Category: Computers

Page: 1382

View: 727

Data Warehousing and Mining (DWM) is the science of managing and analyzing large datasets and discovering novel patterns and in recent years has emerged as a particularly exciting and industrially relevant area of research. Prodigious amounts of data are now being generated in domains as diverse as market research, functional genomics and pharmaceuticals; intelligently analyzing these data, with the aim of answering crucial questions and helping make informed decisions, is the challenge that lies ahead. The Encyclopedia of Data Warehousing and Mining provides a comprehensive, critical and descriptive examination of concepts, issues, trends, and challenges in this rapidly expanding field of data warehousing and mining (DWM). This encyclopedia consists of more than 350 contributors from 32 countries, 1,800 terms and definitions, and more than 4,400 references. This authoritative publication offers in-depth coverage of evolutions, theories, methodologies, functionalities, and applications of DWM in such interdisciplinary industries as healthcare informatics, artificial intelligence, financial modeling, and applied statistics, making it a single source of knowledge and latest discoveries in the field of DWM.
Categories: Computers

Introduction to Clustering Large and High Dimensional Data

Introduction to Clustering Large and High Dimensional Data

Focuses on a few of the important clustering algorithms in the context of information retrieval.

Author: Jacob Kogan

Publisher: Cambridge University Press

ISBN: 0521617936

Category: Computers

Page: 205

View: 115

Focuses on a few of the important clustering algorithms in the context of information retrieval.
Categories: Computers

Multidimensional Data Representations

Multidimensional Data Representations

Invariance of Parameters Are the parameter values of the one-dimensional
groups, Groups H and V, equal to those of the two-dimensional group, Group HV
? This question of parameter invariance across the different groups can be
answered ...

Author: Ingwer Borg

Publisher:

ISBN: UOM:39015004196989

Category: Multidimensional scaling

Page: 695

View: 838

Categories: Multidimensional scaling

Transactions on Large Scale Data and Knowledge Centered Systems VIII

Transactions on Large Scale Data  and Knowledge Centered Systems VIII

A wealth of multidimensional OLAP models has been suggested in the past,
tackling various problems of modeling multidimensional data. However, all of
these models focus on navigational and query operators for grouping, selection
and ...

Author: Abdelkader Hameurlain

Publisher: Springer

ISBN: 9783642375743

Category: Computers

Page: 197

View: 336

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the eighth issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains eight revised selected regular papers focusing on the following topics: scalable data warehousing via MapReduce, extended OLAP multidimensional models, naive OLAP engines and their optimization, advanced data stream processing and mining, semi-supervised learning of data streams, incremental pattern mining over data streams, association rule mining over data streams, frequent pattern discovery over data streams.
Categories: Computers

Multidimensional Executive Coaching

Multidimensional Executive Coaching

communication patterns, human energy, emotional state, intergroup dynamics,
unconscious basic assumptions, time ... term “parallel process” and demonstrates
how observing individuals and groups can give crucial data about dynamics at a
 ...

Author: Ruth L. Orenstein, PsyD

Publisher: Springer Publishing Company

ISBN: 0826125670

Category: Psychology

Page: 234

View: 156

According to a recent study, there is a 40% failure rate among executives in the U.S. today. To combat the difficulties inherent in assuming high-level corporate roles companies are using new tools to help executives achieve maximum effectiveness, including the hiring of an executive coach. This unique book, written by a trained psychologist and executive coach with decades of experience as a business executive, offers a step-by-step guide to the practice of executive coaching. Using actual case studies, the author builds a multidimensional approach to coaching; clients are encouraged to look at multiple forces in their lives, including the Individual and the Organization, Unconscious Forces, Multi-Level Forces, and their Use of Self. Examining each force then guides the executive coach in joint goal setting, commitment to a coaching contract, meeting objectives, evaluating outcomes, and concluding the coaching process. Written specifically for graduate students--of applied psychology and related disciplines--who wish to practice executive coaching, this text will enlighten anyone in business who would like to use executive coaching to improve his or her organization.
Categories: Psychology

High Performance Computing and Networking

High Performance Computing and Networking

Visual. Clustering. of. Multidimensional. and. Large. Data. Sets. Using. Parallel.
Environments. J. Blasiak,. W. Dzwinel ... The role of clustering is to extract the
groups of data (multidimensional points) - clusters - in the feature space to
determine ...

Author: Peter Sloot

Publisher: Springer Science & Business Media

ISBN: 3540644431

Category: Computers

Page: 1039

View: 490

Proceedings -- Parallel Computing.
Categories: Computers

Optical Diagnostics of Living Cells

Optical Diagnostics of Living Cells

While the multidimensional data points do show some grouping the probability
for all of the measurements being identical for even two cells within the
measurement resolution ( typically 8 - to 12 - bit resolution for each measurement
) is very ...

Author:

Publisher:

ISBN: UOM:39015047800043

Category: Cytology

Page:

View: 119

Categories: Cytology

Proceedings of the 1996 ACM CIKM International Conference on Information and Knowledge Management

Proceedings of the 1996 ACM CIKM International Conference on Information and Knowledge Management

This paper formalizes a multidimensional data ( MDD ) model for OLAP , and
develops an algebraic query language called grouping algebra . The basic
component of the MDD model is a multidimensional cube , consisting of a
number of ...

Author: Association for Computing Machinery

Publisher: Assn for Computing Machinery

ISBN: PSU:000031098014

Category: Database management

Page: 344

View: 430

Categories: Database management

Exploratory Data Analysis with MATLAB

Exploratory Data Analysis with MATLAB

We now turn our attention to the problem of finding groups or clusters in our data,
which is an important method in EDA ... is universally appropriate for finding all
varieties of groupings that can be represented by multidimensional data [Jain, ...

Author: Wendy L. Martinez

Publisher: CRC Press

ISBN: 9781135440183

Category: Business & Economics

Page: 424

View: 698

Exploratory data analysis (EDA) was conceived at a time when computers were not widely used, and thus computational ability was rather limited. As computational sophistication has increased, EDA has become an even more powerful process for visualizing and summarizing data before making model assumptions to generate hypotheses, encompassing larger and more complex data sets. There are many resources for those interested in the theory of EDA, but this is the first book to use MATLAB to illustrate the computational aspects of this discipline. Exploratory Data Analysis with MATLAB presents the methods of EDA from a computational perspective. The authors extensively use MATLAB code and algorithm descriptions to provide state-of-the-art techniques for finding patterns and structure in data. Addressing theory, they also incorporate many annotated references to direct readers to the more theoretical aspects of the methods. The book presents an approach using the basic functions from MATLAB and the MATLAB Statistics Toolbox, in order to be more accessible and enduring. It also contains pseudo-code to enable users of other software packages to implement the algorithms. This text places the tools needed to implement EDA theory at the fingertips of researchers, applied mathematicians, computer scientists, engineers, and statisticians by using a practical/computational approach.
Categories: Business & Economics

Data Warehousing and Knowledge Discovery

Data Warehousing and Knowledge Discovery

Since data warehousing has become a major field of research there has been a
lot of interest in the selection of ... lattice is a DAG showing the dependencies
among the sets of grouping attributes (granularities) in a multidimensional
database.

Author: Yahiko Kambayashi

Publisher: Springer Science & Business Media

ISBN: 9783540679806

Category: Computers

Page: 440

View: 187

The Second International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2000) was held in Greenwich, UK 4–6 September. DaWaK 2000 was a forum where researchers from data warehousing and knowledge discovery disciplines could exchange ideas on improving next generation decision support and data mining systems. The conference focused on the logical and physical design of data warehousing and knowledge discovery systems. The scope of the papers covered the most recent and relevant topics in the areas of data warehousing, multidimensional databases, OLAP, knowledge discovery and mining complex databases. These proceedings contain the technical papers selected for presentation at the conference. We received more than 90 papers from over 20 countries and the program committee finally selected 31 long papers and 11 short papers. The conference program included three invited talks, namely, “A Foolish Consistency: Technical Challenges in Consistency Management” by Professor Anthony Finkelstein, University College London, UK; “European Plan for Research in Data Warehousing and Knowledge Discovery” by Dr. Harald Sonnberger (Head of Unit A4, Eurostat, European Commission); and “Security in Data Warehousing” by Professor Bharat Bhargava, Purdue University, USA.
Categories: Computers

Static and Dynamic Lateral Loading of Pile Groups

Static and Dynamic Lateral Loading of Pile Groups

The breakout groups were asked to identify data and functional requirements for
a multimodal , multidimensional LRS data model as the data and functional
requirements relate to the stakeholders . Figure 1-1 shows the four - phase
activity ...

Author:

Publisher:

ISBN: UCBK:C100903335

Category: Bridges

Page:

View: 441

Categories: Bridges

Bulletin de L Institut International de Statistique

Bulletin de L Institut International de Statistique

With Grand Tour , we can explore the structure of multidimensional data
projected in a two dimensional window . ... The first snapshot strongly suggests
the existence of data grouping , and the second snapshot suggests there are a
few points ...

Author: International Statistical Institute

Publisher:

ISBN: STANFORD:36105110566473

Category: Statistics

Page:

View: 593

V. 1-5, v. 7-10 include "Bulletin bibliographique."
Categories: Statistics

Actes de la Session

Actes de la Session

4 Size Group 1 ( red ) 87 Group 2 ( blue ) | 313 I Total 1 400 Age 28 . 3 31 . 7 | 30
. 9 Coll . ... Third method is Grand Tour . With Grand Tour , we can explore the
structure of multidimensional data projected in a two dimensional window .

Author: International Statistical Institute

Publisher:

ISBN: UOM:39015079388560

Category: Statistics

Page:

View: 117

Categories: Statistics