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Claudio Carpineto Concept Data Analysis


With the advent of the Web along with the unprecedented amount of information available in electronic format, conceptual data analysis is more useful and practical than ever, because this technology addresses important limitations of the systems that currently support users in their quest for information. Concept Data Analysis: Theory & Applications is the first book that provides a comprehensive treatment of the full range of algorithms available for conceptual data analysis, spanning creation, maintenance, display and manipulation of concept lattices. The accompanying website allows you to gain a greater understanding of the principles covered in the book through actively working on the topics discussed. The three main areas explored are interactive mining of documents or collections of documents (including Web documents), automatic text ranking, and rule mining from structured data. The potentials of conceptual data analysis in the application areas being considered are further illustrated by two detailed case studies. Concept Data Analysis: Theory & Applications is essential for researchers active in information processing and management and industry practitioners who are interested in creating a commercial product for conceptual data analysis or developing content management applications.

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Gerardus Blokdyk Concept Analysis A Complete Guide - 2020 Edition


How do you measure lifecycle phases? What role does communication play in the success or failure of a Concept analysis project? What are the potential basics of Concept analysis fraud? What are the costs of reform? How do you verify the authenticity of the data and information used? This astounding Concept Analysis self-assessment will make you the assured Concept Analysis domain specialist by revealing just what you need to know to be fluent and ready for any Concept Analysis challenge. How do I reduce the effort in the Concept Analysis work to be done to get problems solved? How can I ensure that plans of action include every Concept Analysis task and that every Concept Analysis outcome is in place? How will I save time investigating strategic and tactical options and ensuring Concept Analysis costs are low? How can I deliver tailored Concept Analysis advice instantly with structured going-forward plans? There’s no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Concept Analysis essentials are covered, from every angle: the Concept Analysis self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Concept Analysis outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Concept Analysis practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Concept Analysis are maximized with professional results. Your purchase includes access details to the Concept Analysis self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: – The latest quick edition of the book in PDF – The latest complete edition of the book in PDF, which criteria correspond to the criteria in… – The Self-Assessment Excel Dashboard – Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation – In-depth and specific Concept Analysis Checklists – Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

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Hyunjoung Lee Fundamentals of Big Data Network Analysis for Research and Industry


Fundamentals of Big Data Network Analysis for Research and Industry Hyunjoung Lee, Institute of Green Technology, Yonsei University, Republic of Korea Il Sohn, Material Science and Engineering, Yonsei University, Republic of Korea Presents the methodology of big data analysis using examples from research and industry There are large amounts of data everywhere, and the ability to pick out crucial information is increasingly important. Contrary to popular belief, not all information is useful; big data network analysis assumes that data is not only large, but also meaningful, and this book focuses on the fundamental techniques required to extract essential information from vast datasets. Featuring case studies drawn largely from the iron and steel industries, this book offers practical guidance which will enable readers to easily understand big data network analysis. Particular attention is paid to the methodology of network analysis, offering information on the method of data collection, on research design and analysis, and on the interpretation of results. A variety of programs including UCINET, NetMiner, R, NodeXL, and Gephi for network analysis are covered in detail. Fundamentals of Big Data Network Analysis for Research and Industry looks at big data from a fresh perspective, and provides a new approach to data analysis. This book: Explains the basic concepts in understanding big data and filtering meaningful data Presents big data analysis within the networking perspective Features methodology applicable to research and industry Describes in detail the social relationship between big data and its implications Provides insight into identifying patterns and relationships between seemingly unrelated big data Fundamentals of Big Data Network Analysis for Research and Industry will prove a valuable resource for analysts, research engineers, industrial engineers, marketing professionals, and any individuals dealing with accumulated large data whose interest is to analyze and identify potential relationships among data sets.

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Yuichi Motai Data-Variant Kernel Analysis


Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent years This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications. The book surveys the current status, popular trends, and developments in kernel analysis studies. The author discusses multiple kernel learning algorithms and how to choose the appropriate kernels during the learning phase. Data-Variant Kernel Analysis is a new pattern analysis framework for different types of data configurations. The chapters include data formations of offline, distributed, online, cloud, and longitudinal data, used for kernel analysis to classify and predict future state. Data-Variant Kernel Analysis: Surveys the kernel analysis in the traditionally developed machine learning techniques, such as Neural Networks (NN), Support Vector Machines (SVM), and Principal Component Analysis (PCA) Develops group kernel analysis with the distributed databases to compare speed and memory usages Explores the possibility of real-time processes by synthesizing offline and online databases Applies the assembled databases to compare cloud computing environments Examines the prediction of longitudinal data with time-sequential configurations Data-Variant Kernel Analysis is a detailed reference for graduate students as well as electrical and computer engineers interested in pattern analysis and its application in colon cancer detection.

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Bendat Julius S. Random Data. Analysis and Measurement Procedures


A timely update of the classic book on the theory and application of random data analysis First published in 1971, Random Data served as an authoritative book on the analysis of experimental physical data for engineering and scientific applications. This Fourth Edition features coverage of new developments in random data management and analysis procedures that are applicable to a broad range of applied fields, from the aerospace and automotive industries to oceanographic and biomedical research. This new edition continues to maintain a balance of classic theory and novel techniques. The authors expand on the treatment of random data analysis theory, including derivations of key relationships in probability and random process theory. The book remains unique in its practical treatment of nonstationary data analysis and nonlinear system analysis, presenting the latest techniques on modern data acquisition, storage, conversion, and qualification of random data prior to its digital analysis. The Fourth Edition also includes: A new chapter on frequency domain techniques to model and identify nonlinear systems from measured input/output random data New material on the analysis of multiple-input/single-output linear models The latest recommended methods for data acquisition and processing of random data Important mathematical formulas to design experiments and evaluate results of random data analysis and measurement procedures Answers to the problem in each chapter Comprehensive and self-contained, Random Data, Fourth Edition is an indispensible book for courses on random data analysis theory and applications at the upper-undergraduate and graduate level. It is also an insightful reference for engineers and scientists who use statistical methods to investigate and solve problems with dynamic data.

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Johnson Wayne P. Making Sense of Data I. A Practical Guide to Exploratory Data Analysis and Data Mining


Praise for the First Edition “…a well-written book on data analysis and data mining that provides an excellent foundation…” —CHOICE “This is a must-read book for learning practical statistics and data analysis…” —Computing Reviews.com A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors’ practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide readers from almost every field of study. In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. The tools to summarize and interpret data in order to master data analysis are integrated throughout, and the Second Edition also features: Updated exercises for both manual and computer-aided implementation with accompanying worked examples New appendices with coverage on the freely available Traceis™ software, including tutorials using data from a variety of disciplines such as the social sciences, engineering, and finance New topical coverage on multiple linear regression and logistic regression to provide a range of widely used and transparent approaches Additional real-world examples of data preparation to establish a practical background for making decisions from data Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition is an excellent reference for researchers and professionals who need to achieve effective decision making from data. The Second Edition is also an ideal textbook for undergraduate and graduate-level courses in data analysis and data mining and is appropriate for cross-disciplinary courses found within computer science and engineering departments.

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Michael J. Albers Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences


Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data to the appropriate statistical tests, and drawing valid conclusions Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool for analyzing research data. The book presents the entire data analysis process as a cyclical, multiphase process and addresses the processes of exploratory analysis, decision-making for performing parametric or nonparametric analysis, and practical significance determination. In addition, the author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the data’s contextual situation. Filling the gap in quantitative data analysis literature, this book teaches the methods and thought processes behind data analysis, rather than how to perform the study itself or how to perform individual statistical tests. With a clear and conversational style, readers are provided with a better understanding of the overall structure and methodology behind performing a data analysis as well as the needed techniques to make informed, meaningful decisions during data analysis. The book features numerous data analysis examples in order to emphasize the decision and thought processes that are best followed, and self-contained sections throughout separate the statistical data analysis from the detailed discussion of the concepts allowing readers to reference a specific section of the book for immediate solutions to problems and/or applications. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences also features coverage of the following: • The overall methodology and research mind-set for how to approach quantitative data analysis and how to use statistics tests as part of research data analysis • A comprehensive understanding of the data, its connection to a research situation, and the most appropriate statistical tests for the data • Numerous data analysis problems and worked-out examples to illustrate the decision and thought processes that reveal underlying patterns and trends • Detailed examples of the main concepts to aid readers in gaining the needed skills to perform a full analysis of research problems • A conversational tone to effectively introduce readers to the basics of how to perform data analysis as well as make meaningful decisions during data analysis Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences is an ideal textbook for upper-undergraduate and graduate-level research method courses in the behavioral and social sciences, statistics, and engineering. This book is also an appropriate reference for practitioners who require a review of quantitative research methods. Michael J. Albers, Ph.D., is Professor in the Department of English at East Carolina University. His research interests include information design with a focus on answering real-world questions, the presentation of complex information, and human–information interaction. Dr. Albers received his Ph.D. in Technical Communication and Rhetoric from Texas Tech University.

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Galit Shmueli Information Quality


Provides an important framework for data analysts in assessing the quality of data and its potential to provide meaningful insights through analysis Analytics and statistical analysis have become pervasive topics, mainly due to the growing availability of data and analytic tools. Technology, however, fails to deliver insights with added value if the quality of the information it generates is not assured. Information Quality (InfoQ) is a tool developed by the authors to assess the potential of a dataset to achieve a goal of interest, using data analysis. Whether the information quality of a dataset is sufficient is of practical importance at many stages of the data analytics journey, from the pre-data collection stage to the post-data collection and post-analysis stages. It is also critical to various stakeholders: data collection agencies, analysts, data scientists, and management. This book: Explains how to integrate the notions of goal, data, analysis and utility that are the main building blocks of data analysis within any domain. Presents a framework for integrating domain knowledge with data analysis. Provides a combination of both methodological and practical aspects of data analysis. Discusses issues surrounding the implementation and integration of InfoQ in both academic programmes and business / industrial projects. Showcases numerous case studies in a variety of application areas such as education, healthcare, official statistics, risk management and marketing surveys. Presents a review of software tools from the InfoQ perspective along with example datasets on an accompanying website. This book will be beneficial for researchers in academia and in industry, analysts, consultants, and agencies that collect and analyse data as well as undergraduate and postgraduate courses involving data analysis.

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Группа авторов Data Analysis


The first part of this book is devoted to methods seeking relevant dimensions of data. The variables thus obtained provide a synthetic description which often results in a graphical representation of the data. After a general presentation of the discriminating analysis, the second part is devoted to clustering methods which constitute another method, often complementary to the methods described in the first part, to synthesize and to analyze the data. The book concludes by examining the links existing between data mining and data analysis.

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Lawrence S. Meyers Performing Data Analysis Using IBM SPSS


Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS® Performing Data Analysis Using IBM SPSS® uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets. Data entry procedures, variable naming, and step-by-step instructions for all analyses are provided in addition to IBM SPSS point-and-click methods, including details on how to view and manipulate output. Designed as a user’s guide for students and other interested readers to perform statistical data analysis with IBM SPSS, this book addresses the needs, level of sophistication, and interest in introductory statistical methodology on the part of readers in social and behavioral science, business, health-related, and education programs. Each chapter of Performing Data Analysis Using IBM SPSS covers a particular statistical procedure and offers the following: an example problem or analysis goal, together with a data set; IBM SPSS analysis with step-by-step analysis setup and accompanying screen shots; and IBM SPSS output with screen shots and narrative on how to read or interpret the results of the analysis. The book provides in-depth chapter coverage of: IBM SPSS statistical output Descriptive statistics procedures Score distribution assumption evaluations Bivariate correlation Regressing (predicting) quantitative and categorical variables Survival analysis t Test ANOVA and ANCOVA Multivariate group differences Multidimensional scaling Cluster analysis Nonparametric procedures for frequency data Performing Data Analysis Using IBM SPSS is an excellent text for upper-undergraduate and graduate-level students in courses on social, behavioral, and health sciences as well as secondary education, research design, and statistics. Also an excellent reference, the book is ideal for professionals and researchers in the social, behavioral, and health sciences; applied statisticians; and practitioners working in industry.

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Concept data analysis. Theory and application | Claudio ...

Concept data analysis. Theory and application. Claudio Carpineto, Giovanni Romano. "With the advent of the Web along with the unprecedented amount of information available in electronic format, conceptual data analysis is more useful and practical than ever, because this technology addresses important limitations of the systems that currently ...

Concept Data Analysis: Theory and Applications - Claudio ...

Claudio Carpineto is the head of the Information mining group at Fondazione Ugo Bordoni, in Rome. He has published numerous articles on artificial intelligence. Giovanni Romano is the author of...

Claudio Carpineto > concept | PUMA

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A lattice conceptual clustering system and its application ...

CLAUDIO CARPINETO [email protected] GIOVANNI ROMANO [email protected] Fondazione Ugo Bordoni, Via Baldassarre Castiglione 59, 00142 Rome, Italy Running head: LATTICE CLUSTERING FOR BROWSING. Page 2 Abstract. The theory of concept (or Galois) lattices provides a simple and formal approach to conceptual clustering. In this paper we present GALOIS, a system that automates and applies this theory. The ...

Concept Data Analysis von Claudio Carpineto; Giovanni ...

With the advent of the Web along with the unprecedented amount of information available in electronic format, conceptual data analysis is more useful and practical than ever, because this technology addresses important limitations of the systems that currently support users in their quest for information.

Publications by Claudio Carpineto

Amati , G., Carpineto, C., and Romano, G. (2004). Query difficulty, robustness and selective application of query expansion. Proceedings of the 25th European Conference on Information Retrieval (ECIR 2004), Sunderland, Great Britain, pp. 127-137. Test of Time award at ECIR 2016 pdf; Carpineto, C., Romano, G. (2013). Semantic Search Log k-Anonymization with Generalized k-Cores of Query Concept ...

Concept Data Analysis by Carpineto, Claudio (ebook)

Concept Data Analysis: Theory and Applications by Claudio Carpineto. With the advent of the Web along with the unprecedented amount of information available in electronic format, conceptual data analysis is more useful and practical than ever, because this technology addresses important limitations of the systems that currently support users in their quest for information. Concept Data ...

(PDF) Automatic Construction of Navigable Concept Networks ...

Claudio Carpineto Giovanni Romano In this paper we describe an approach, implemented in a system named REFINER, to combining Boolean information retrieval and content-based navigation with concept ...

Concept Data Analysis (eBook, PDF) von Claudio Carpineto ...

With the advent of the Web along with the unprecedented amount ofinformation available in electronic format, conceptual dataanalysis is more useful and practical than ever, because thistechnology addresses important limitations of the systems thatcurrently support users in their quest for information.

A Concept Lattice-Based Kernel for SVM Text Classification ...

A Concept Lattice-Based Kernel for SVM Text Classification. Share on. Authors: Claudio Carpineto. Fondazione Ugo Bordoni, Rome, Italy. Fondazione Ugo Bordoni, Rome, Italy. View Profile, Carla Michini ...

Concept Data Analysis von Claudio Carpineto | ISBN 978-0 ...

Concept Data Analysis von Claudio Carpineto, Giovanni Romano (ISBN 978-0-470-85055-8) bestellen. Schnelle Lieferung, auch auf Rechnung - lehmanns.de

Concept Data Analysis: Theory and Applications: Amazon.de ...

Concept Data Analysis: Theory and Applications | Carpineto, Claudio, Romano, Giovanni | ISBN: 9780470850558 | Kostenloser Versand für alle Bücher mit Versand und Verkauf duch Amazon.

Concept Data Analysis: Theory and Applications / Edition 1 ...

Claudio Carpineto. is the head of the Information mining group at Fondazione Ugo Bordoni, in Rome. He has published numerous articles on artificial intelligence. Giovanni Romano is the author of Concept Data Analysis: Theory and Applications, published by Wiley.

Claudio Carpineto | PUMA

Claudio Carpineto × Publication title ... ascending; descending; help for advanced sorting... RSS; BibTeX; RDF; more... 2 Concept Data Analysis: Theory and Applications C. Carpineto, and G. Romano. John Wiley & Sons, Chichester, England; Hoboken, NJ, (2004) 9 years ago by @stephandoerfel × Close. icfca fca carpineto. copy delete add this publication to your clipboard. community post ...

Concept Data Analysis: Theory and Applications: Carpineto ...

Concept Data Analysis: Theory and Applications [Carpineto, Claudio, Romano, Giovanni] on Amazon.com. *FREE* shipping on qualifying offers. Concept Data Analysis: Theory and Applications

Concept Data Analysis: Theory and Applications | Database ...

Claudio Carpineto is the head of the Information mining group at Fondazione Ugo Bordoni, in Rome. He has published numerous articles on artificial intelligence. Giovanni Romano is the author of Concept Data Analysis: Theory and Applications, published by Wiley.

FCAIR 2012 – Formal Concept Analysis Meets ... - CORE

FCAIR 2012 – Formal Concept Analysis Meets Information Retrieval By Claudio Carpineto, Sergei O. Kuznetsov, Amedeo Napoli (eds, Claudio Carpineto, Sergei O. Kuznetsov and Amedeo Napoli Abstract

‪Claudio Carpineto‬ - ‪Google Scholar‬

Claudio Carpineto. Fondazione Ugo Bordoni. Verified email at fub.it. information retrieval data mining artificial intelligence formal concept analysis data privacy. Articles Cited by. Title. Sort . Sort by citations Sort by year Sort by title. Cited by. Cited by. Year; A survey of automatic query expansion in information retrieval. C Carpineto, G Romano. Acm Computing Surveys (CSUR) 44 (1), 1 ...

(PDF) A Concept Lattice-Based Kernel for SVM Text ...

10 Claudio Carpineto et al. 4.3 Construction of document lattice Once each document has been represented with a set of predictive features, we partition the entire dataset in training and test sets, and construct the concept lattice associated with the training set. To build the document lattice, we use the NextNeighbors algorithm, described in [4] on page 35. 4.4 Pairwise term proximity To ...

Concept Data Analysis: Theory and Applications (English ...

Concept Data Analysis: Theory and Applications (English Edition) eBook: Carpineto, Claudio, Romano, Giovanni: Amazon.de: Kindle-Shop

CiteSeerX — Using concept lattices for text retrieval and ...

BibTeX @INPROCEEDINGS{Carpineto05usingconcept, author = {Claudio Carpineto and Giovanni Romano}, title = {Using concept lattices for text retrieval and mining}, booktitle = {IN FORMAL CONCEPT ANALYSIS-STATE OF THE ART, PROC. OF THE FIRST INTERNATIONAL CONFERENCE ON FORMAL CONCEPT ANALYSIS}, year = {2005}, publisher = {Springer}}

CiteSeerX — Search Results — Exploiting the Potential of ...

by Claudio Carpineto, Giovanni Romano - IN FORMAL CONCEPT ANALYSIS-STATE OF THE ART, PROC. OF THE FIRST INTERNATIONAL CONFERENCE ON FORMAL CONCEPT ANALYSIS , 2005 The potentials of formal concept analysis (FCA) for information retrieval (IR) have been highlighted by a number of research studies since its inception.

Claudio Carpineto - researchr alias

Filter by Year. OR AND NOT 1. 1988

eBook: Concept Data Analysis von Claudio Carpineto | ISBN ...

Concept Data Analysis von Claudio Carpineto, Giovanni Romano (ISBN 978-0-470-01128-7) online kaufen | Sofort-Download - lehmanns.de

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Add open access links from to the list of external document links (if available). load links from unpaywall.org. Privacy notice: By enabling the option above, your ...

Introduction to Formal Concept Analysis - International ...

Claudio Carpineto and Giovanni Romano, Concept Data Analysis: Theory and Applications, Wiley, 2004. Proceedings of the International Conference on Formal Concept Analysis, Lecture Notes in Computer Science, Springer, Berlin/Heidelberg, 2004-2012.

Claudio CARPINETO | Fondazione Ugo Bordoni, Rome | FUB ...

Claudio Carpineto Giovanni Romano An implication rule QR is roughly a statement of the form "for all objects in the database, if an object has Q then it has also R".

Effective Reformulation of Boolean Queries with Concept ...

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): In this paper we describe an approach, implemented in a system named REFINER, to combining Boolean information retrieval and content-based navigation with concept lattices. When REFINER i s presented with a Boolean query, it builds and displays a portion of the concept lattice associated with the documents being ...

Formal concept analysis - Wikipedia

Formal concept analysis (FCA) is a principled way of deriving a concept hierarchy or formal ontology from a collection of objects and their properties.Each concept in the hierarchy represents the objects sharing some set of properties; and each sub-concept in the hierarchy represents a subset of the objects (as well as a superset of the properties) in the concepts above it.

Concept Data Analysis: Theory and Applications by Claudio ...

Concept Data Analysis book. Read reviews from world’s largest community for readers. With the advent of the Web along with the unprecedented amount of in...

Semantic Search Log k-Anonymization with Generalized k ...

Generalized k-Cores of Query Concept Graph Claudio Carpineto and Giovanni Romano Fondazione Ugo Bordoni, Rome, Italy {carpinet, romano}@fub.it Abstract. Search log k-anonymization is based on the elimination of infrequent queries under exact (or nearly exact) matching conditions, which usually results in a big data loss and impaired utility. We present a more flexible, semantic approach to k ...

Effective reformulation of Boolean queries with concept ...

Effective reformulation of Boolean queries with concept lattices . By Claudio Carpineto and Giovanni Romano. Cite . BibTex; Full citation; Publisher: Springer Berlin Heidelberg. Year: 2006. DOI identifier: 10.1007/bfb0055993. OAI identifier: Provided by: MUCC (Crossref) ...

9780470850558: Concept Data Analysis: Theory and ...

AbeBooks.com: Concept Data Analysis: Theory and Applications (9780470850558) by Carpineto, Claudio; Romano, Giovanni and a great selection of similar New, Used and Collectible Books available now at great prices.

Claudio Carpineto (Author of Concept Data Analysis)

Claudio Carpineto is the author of Concept Data Analysis (3.20 avg rating, 5 ratings, 0 reviews, published 2004)

Concept Data Analysis : Claudio Carpineto : 9780470850558

Concept Data Analysis by Claudio Carpineto, 9780470850558, available at Book Depository with free delivery worldwide.

Concept Data Analysis - ISBN: 9780470011287 - (ebook ...

Concept Data Analysis - ISBN: 9780470011287 - (ebook) - von Claudio Carpineto, Giovanni Romano, Verlag: Wiley

FCAIR 2012 { Formal Concept Analysis Meets Information ...

Claudio Carpineto, Sergei O. Kuznetsov, Amedeo Napoli (Eds.) FCAIR 2012 { Formal Concept Analysis Meets Information Retrieval Workshop co-located with the 35th European Conference on Information Re- trieval (ECIR 2013) March 24, 2013, Moscow, Russia. Volume Editors Claudio Carpineto Fondazione Ugo Bordoni, Rome, Italy Sergei O. Kuznetsov School of Applied Mathematics and Information Science ...

Formale Begriffsanalyse – Wikipedia

Die Formale Begriffsanalyse (abgekürzt FBA) (englisch Formal Concept Analysis, abgekürzt FCA), ist eine mathematische Theorie.Sie liefert eine Methodik, um Zusammenhänge in gegebenen Datenmengen zu erkennen.Typisch dafür sind hierarchische Beziehungen zwischen Begriffen.Die Formale Begriffsanalyse kann als angewandte Ordnungs-und Verbandstheorie verstanden werden.

Description: Concept data analysis

Concept data analysis : theory and applications [E-Book] / Claudio Carpineto, Giovanni Romano. Concept data analysis : theory and applications [E-Book] / Claudio Carpineto, Giovanni Romano.

Figure 3 from A lattice conceptual clustering system and ...

DOI: 10.1007/BF00058654 Corpus ID: 2928016. A lattice conceptual clustering system and its application to browsing retrieval @article{Carpineto2004ALC, title={A lattice conceptual clustering system and its application to browsing retrieval}, author={Claudio Carpineto and G. Romano}, journal={Machine Learning}, year={2004}, volume={24}, pages={95-122} }

Table 3 from A lattice conceptual clustering system and ...

DOI: 10.1007/BF00058654 Corpus ID: 2928016. A lattice conceptual clustering system and its application to browsing retrieval @article{Carpineto2004ALC, title={A lattice conceptual clustering system and its application to browsing retrieval}, author={Claudio Carpineto and G. Romano}, journal={Machine Learning}, year={2004}, volume={24}, pages={95-122} }

Order‐theoretical ranking - Carpineto - 2000 - Journal of ...

Current best‐match ranking (BMR) systems perform well but cannot handle word mismatch between a query and a document. The best known alternative ranking method, hierarchical clustering‐based ranking ...

CEUR-WS.org/Vol-977 - Workshop Formal Concept Analysis ...

Claudio Carpineto; Invited Papers. New Applications of Formal Concept Analysis: A Need for Original Pattern Domains (extended abstract) 2-4 Jean-Francois Boulicaut; Key Phrase to Text Similarity, Clustering, and Interpretation in Hierarchical Ontologies (abstract) 5 Boris Mirkin; Regular Papers . Improving Text Retrieval Efficiency with Pattern Structures on Parse Thickets 6-21 Boris A ...

Concept Data Analysis | Wiley Online Books

Concept Data Analysis: Theory & Applications is the first book that provides a comprehensive treatment of the full range of algorithms available for conceptual data analysis, spanning creation, maintenance, display and manipulation of concept lattices. The accompanying website allows you to gain a greater understanding of the principles covered in the book through actively working on the ...

Semantic Search Log k-Anonymization with Generalized k ...

Claudio Carpineto. 1; Giovanni Romano. 1; 1. Fondazione Ugo Bordoni Rome Italy; About this paper . Cite this paper as: Carpineto C., Romano G. (2013) Semantic Search Log k-Anonymization with Generalized k-Cores of Query Concept Graph. In: Serdyukov P. et al. (eds) Advances in Information Retrieval. ECIR 2013. Lecture Notes in Computer Science, vol 7814. Springer, Berlin, Heidelberg. https ...

Table of Contents - GBV

Claudio Carpineto Formal Concept Analysis on Its Way from Mathematics to Computer Science 2 Gerd Stumme Data and Knowledge Structures A Linearly Complex Model for Knowledge Representation 20 Janos Sarbo and Jözsef Parkas Relation Graphs: A Structure for Representing Relations in Contextual Logic of Relations 34 Silke Pollandt Information Transfer across Simple Concept Graphs 48 Grit Malik ...

Mobile Clustering Engine | SpringerLink

Claudio Carpineto; Andrea Della Pietra; Stefano Mizzaro; Giovanni Romano; Conference paper. 5 Citations; 1.2k Downloads; Part of the Lecture Notes in Computer Science book series (LNCS, volume 3936) Abstract. Although mobile information retrieval is seen as the next frontier of the search market, the rendering of results on mobile devices is still unsatisfactory. We present Credino, a ...

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Группа авторов Applied Multiway Data Analysis


From a preeminent authority—a modern and applied treatment of multiway data analysis This groundbreaking book is the first of its kind to present methods for analyzing multiway data by applying multiway component techniques. Multiway analysis is a specialized branch of the larger field of multivariate statistics that extends the standard methods for two-way data, such as component analysis, factor analysis, cluster analysis, correspondence analysis, and multidimensional scaling to multiway data. Applied Multiway Data Analysis presents a unique, thorough, and authoritative treatment of this relatively new and emerging approach to data analysis that is applicable across a range of fields, from the social and behavioral sciences to agriculture, environmental sciences, and chemistry. General introductions to multiway data types, methods, and estimation procedures are provided in addition to detailed explanations and advice for readers who would like to learn more about applying multiway methods. Using carefully laid out examples and engaging applications, the book begins with an introductory chapter that serves as a general overview of multiway analysis, including the types of problems it can address. Next, the process of setting up, carrying out, and evaluating multiway analyses is discussed along with commonly encountered issues, such as preprocessing, missing data, model and dimensionality selection, postprocessing, and transformation, as well as robustness and stability issues. Extensive examples are presented within a unified framework consisting of a five-step structure: objectives; data description and design; model and dimensionality selection; results and their interpretation; and validation. Procedures featured in the book are conducted using 3WayPack, which is software developed by the author, and analyses can also be carried out within the R and MATLAB systems. Several data sets and 3WayPack can be downloaded via the book's related Web site. The author presents the material in a clear, accessible style without unnecessary or complex formalism, assuring a smooth transition from well-known standard two-analysis to multiway analysis for readers from a wide range of backgrounds. An understanding of linear algebra, statistics, and principal component analyses and related techniques is assumed, though the author makes an effort to keep the presentation at a conceptual, rather than mathematical, level wherever possible. Applied Multiway Data Analysis is an excellent supplement for component analysis and statistical multivariate analysis courses at the upper-undergraduate and beginning graduate levels. The book can also serve as a primary reference for statisticians, data analysts, methodologists, applied mathematicians, and social science researchers working in academia or industry. Visit the Related Website: http://three-mode.leidenuniv.nl/, to view data from the book.

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Группа авторов Data Analysis and Applications 1

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