Classification as a Tool of Research

Classification as a Tool of Research PDF Author: Classification Society. Meeting
Publisher: North Holland
ISBN:
Category : Business & Economics
Languages : en
Pages : 524

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Book Description
This work contains a selection of papers presented at the meeting. The subjects covered include: Data analysis: Methods of scaling, Loglinear models, Correspondence analysis, Pattern recognition and discrimination, Analysis and aggregation of discrete structures, Measures of similarity and association. Numerical classification: Clustering methods, Robustness of methods, Fuzzy clustering, Statistical models. Concept analysis: Construction and reconstruction of concepts, Theories of characteristics and of definitions, Impact on artificial intelligence. Indexing languages and terminologies as information resources: Classification systems, Thesauri, Conceptual structure utilization, Identification of analogies. Software tools (especially on microcomputers): Availability of programs, Interfaces to data base systems, Information retrieval systems, Method base systems, Graphical representation, Comparisons of algorithms. Applications of classification examined here include economics, business administration, natural sciences, social science and humanities, chemistry research, library science, and linguistics. Contributors: P. Arabie, I. Balderjahn, P.M. Bentler, H.-H. Bock, I.

Classification as a Tool of Research

Classification as a Tool of Research PDF Author: Classification Society. Meeting
Publisher: North Holland
ISBN:
Category : Business & Economics
Languages : en
Pages : 524

Get Book Here

Book Description
This work contains a selection of papers presented at the meeting. The subjects covered include: Data analysis: Methods of scaling, Loglinear models, Correspondence analysis, Pattern recognition and discrimination, Analysis and aggregation of discrete structures, Measures of similarity and association. Numerical classification: Clustering methods, Robustness of methods, Fuzzy clustering, Statistical models. Concept analysis: Construction and reconstruction of concepts, Theories of characteristics and of definitions, Impact on artificial intelligence. Indexing languages and terminologies as information resources: Classification systems, Thesauri, Conceptual structure utilization, Identification of analogies. Software tools (especially on microcomputers): Availability of programs, Interfaces to data base systems, Information retrieval systems, Method base systems, Graphical representation, Comparisons of algorithms. Applications of classification examined here include economics, business administration, natural sciences, social science and humanities, chemistry research, library science, and linguistics. Contributors: P. Arabie, I. Balderjahn, P.M. Bentler, H.-H. Bock, I.

Qualitative Research in IS: Issues and Trends

Qualitative Research in IS: Issues and Trends PDF Author: Trauth, Eileen M.
Publisher: IGI Global
ISBN: 1930708947
Category : Science
Languages : en
Pages : 309

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Book Description
This book addresses the need for materials that can help the IS researcher determine which qualitative methods are most appropriate for addressing their particular research questions. It draws upon the collective expertise of distinguished scholars to explore concrete issues they have encountered in the use of a particular qualitative methods. The details of specific research projects provide the backdrop for the discussion of methodological issues. The audience for this book includes students, scholars and researchers. Anyone currently engaged in conducting IS research who would like to learn more about employing qualitative methods will be interested in Qualitative Research in IS: Issues and Trends to learn more about the latest issues and challenges facing IS researchers throughout the world.

Tariff Classification Study ...

Tariff Classification Study ... PDF Author: United States Tariff Commission
Publisher:
ISBN:
Category :
Languages : en
Pages : 1440

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Book Description


Classification-indexing

Classification-indexing PDF Author: Clearinghouse for Federal Scientific and Technical Information (U.S.)
Publisher:
ISBN:
Category : Classification
Languages : en
Pages : 40

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Book Description


Library Classification Trends in the 21st Century

Library Classification Trends in the 21st Century PDF Author: Rajendra Kumbhar
Publisher: Elsevier
ISBN: 1780632983
Category : Language Arts & Disciplines
Languages : en
Pages : 187

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Book Description
Library Classification Trends in the 21st Century traces development in and around library classification as reported in literature published in the first decade of the 21st century. It reviews literature published on various aspects of library classification, including modern applications of classification such as internet resource discovery, automatic book classification, text categorization, modern manifestations of classification such as taxonomies, folksonomies and ontologies and interoperable systems enabling crosswalk. The book also features classification education and an exploration of relevant topics. Covers all aspects of library classification It is the only book that reviews literature published over a decade’s time span (1999-2009) Well thought chapterization which is in tune with the LIS and classification curriculum

Library Support Staff Position Classification Studies

Library Support Staff Position Classification Studies PDF Author:
Publisher: Association of Research Libr
ISBN:
Category : Academic libraries
Languages : en
Pages : 208

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Book Description


Classification Theory

Classification Theory PDF Author: S. Shelah
Publisher: Elsevier
ISBN: 008088024X
Category : Computers
Languages : en
Pages : 741

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Book Description
In this research monograph, the author's work on classification and related topics are presented. This revised edition brings the book up to date with the addition of four new chapters as well as various corrections to the 1978 text.The additional chapters X - XIII present the solution to countable first order T of what the author sees as the main test of the theory. In Chapter X the Dimensional Order Property is introduced and it is shown to be a meaningful dividing line for superstable theories. In Chapter XI there is a proof of the decomposition theorems. Chapter XII is the crux of the matter: there is proof that the negation of the assumption used in Chapter XI implies that in models of T a relation can be defined which orders a large subset of m

WHO Classification of Skin Tumours

WHO Classification of Skin Tumours PDF Author: Centre international de recherche sur le cancer
Publisher: International Agency for Research on Cancer
ISBN: 9789283224402
Category : Medical
Languages : en
Pages : 0

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Book Description
The WHO Classification of Skin Tumours is the 11th volume in the 4th edition of the WHO series on the classification of human tumours. The series (also known as the Blue Books) has long been regarded by pathologists as the gold standard for the diagnosis of tumours, and it is an indispensable guide for the design of evaluations, clinical trials, and studies involving cancer. These authoritative and concise reference books provide an international standard for anyone involved in cancer research or the care of cancer patients. Diagnostic criteria, pathological features, and genetic and other associated molecular alterations are described in a disease-oriented manner. This volume updates the existing ICD-O codes and provides new codes for use in epidemiology and cancer registration. It also provides information on clinical features, pathology, genetics, prognosis, and protective factors for each of the tumour types covered. The editors expect that this volume will be of particular interest to pathologists, oncologists, and dermatologists who manage or research skin tumours. Sections are included on all recognized neoplasms (and their variants) of the skin and its adnexae. Since the previous edition, there have been particularly substantial changes to the classification of melanoma, based on the latest information from genetic and molecular studies.

Advanced Studies in Classification and Data Science

Advanced Studies in Classification and Data Science PDF Author: Tadashi Imaizumi
Publisher: Springer Nature
ISBN: 9811533113
Category : Mathematics
Languages : en
Pages : 506

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Book Description
This edited volume focuses on the latest developments in classification and data science and covers a wide range of topics in the context of data analysis and related areas, e.g. the analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, data visualization, multivariate statistical methods, and various applications to real data in the social sciences, medical sciences, and other disciplines. In addition to sharing theoretical and methodological findings, the book shows how to apply the proposed methods to a variety of problems — e.g. in consumer behavior, decision-making, marketing data and social network structures. Both methodological aspects and applications to a wide range of areas such as economics, behavioral science, marketing science, management science and the social sciences are covered. The book is chiefly intended for researchers and practitioners who are interested in the latest developments and practical applications in these fields, as well as applied statisticians and data analysts. Its combination of methodological advances with a wide range of real-world applications gathered from several fields makes it of unique value in helping readers solve their research problems.

Classification in the Wild

Classification in the Wild PDF Author: Konstantinos V. Katsikopoulos
Publisher: MIT Press
ISBN: 0262361957
Category : Language Arts & Disciplines
Languages : en
Pages : 208

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Book Description
Rules for building formal models that use fast-and-frugal heuristics, extending the psychological study of classification to the real world of uncertainty. This book focuses on classification--allocating objects into categories--"in the wild," in real-world situations and far from the certainty of the lab. In the wild, unlike in typical psychological experiments, the future is not knowable and uncertainty cannot be meaningfully reduced to probability. Connecting the science of heuristics with machine learning, the book shows how to create formal models using classification rules that are simple, fast, and transparent and that can be as accurate as mathematically sophisticated algorithms developed for machine learning.