Linking Sensitive Data: Methods and Techniques for Practical Privacy-Preserving Information Sharing, Christen Peter, Ranbaduge Thilina, Schnell Rainer

Автор: Zhai Chengxiang, Massung Sean
Название: Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
ISBN: 1970001194 ISBN-13(EAN): 9781970001198
Издательство: Mare Nostrum (Eurospan)
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Цена: 103210.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic.This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.

Автор: Pennington Diane
Название: Social Tagging for Linking Data Across Environments
ISBN: 1783303387 ISBN-13(EAN): 9781783303380
Издательство: Facet
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Цена: 109120.00 T
Наличие на складе: Нет в наличии.
Описание: This book, representing researchers and practitioners across different information professions, will explore how social tags can link content across a variety of environments.

Автор: David Wood
Название: Linking Enterprise Data
ISBN: 1489981705 ISBN-13(EAN): 9781489981707
Издательство: Springer
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Цена: 144410.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book methods for applying World Wide Web architecture principles to real-world information management issues faced by commercial, nonprofit and government enterprises. Coverage includes real-world success stories from early enterprise adopters.

Автор: Zhai Chengxiang, Massung Sean
Название: Text Data Management and Analysis: A Practical Introduction to Information Retrieval and Text Mining
ISBN: 197000116X ISBN-13(EAN): 9781970001167
Издательство: Mare Nostrum (Eurospan)
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Цена: 85730.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic.This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.

Автор: Reagan W. Moore, Hao Xu, Mike Conway, Arcot Rajasekar, Jon Crabtree, Helen Tibbo
Название: Trustworthy Policies for Distributed Repositories
ISBN: 1627058850 ISBN-13(EAN): 9781627058858
Издательство: Mare Nostrum (Eurospan)
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Цена: 56370.00 T
Наличие на складе: Невозможна поставка.
Описание: A trustworthy repository provides assurance in the form of management documents, event logs, and audit trails that digital objects are being managed correctly. The assurance includes plans for the sustainability of the repository, the accession of digital records, the management of technology evolution, and the mitigation of the risk of data loss. A detailed assessment is provided by the ISO-16363:2012 standard, "Space data and information transfer systems--Audit and certification of trustworthy digital repositories." This book examines whether the ISO specification for trustworthiness can be enforced by computer actionable policies. An implementation of the policies is provided and the policies are sorted into categories for procedures to manage externally generated documents, specify repository parameters, specify preservation metadata attributes, specify audit mechanisms for all preservation actions, specify control of preservation operations, and control preservation properties as technology evolves. An application of the resulting procedures is made to enforce trustworthiness within National Science Foundation data management plans.

Автор: Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis
Название: Data Exploration Using Example-Based Methods
ISBN: 1681734559 ISBN-13(EAN): 9781681734552
Издательство: Mare Nostrum (Eurospan)
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Цена: 66530.00 T
Наличие на складе: Невозможна поставка.
Описание: Data usually comes in a plethora of formats and dimensions, rendering the information extraction and exploration processes challenging. Thus, being able to perform exploratory analyses of the data with the intent of having an immediate glimpse of some of the data properties is becoming crucial. Exploratory analyses should be simple enough to avoid complicated declarative languages (such as SQL) and mechanisms, while at the same time retaining the flexibility and expressiveness of such languages. Recently, we have witnessed a rediscovery of the so-called example-based methods, in which the user, or analyst, circumvents query languages by using examples as input. An example is a representative of the intended results or, in other words, an item from the result set. Example-based methods exploit inherent characteristics of the data to infer the results that the user has in mind but may not be able to (easily) express. They can be useful in cases where a user is looking for information in an unfamiliar dataset, when they are performing a particularly challenging task like finding duplicate items, or when they are simply exploring the data. In this book, we present an excursus over the main methods for exploratory analysis, with a particular focus on example-based methods. We show how different data types require different techniques and present algorithms that are specifically designed for relational, textual, and graph data. The book also presents the challenges and new frontiers of machine learning in online settings that have recently attracted the attention of the database community. The book concludes with a vision for further research and applications in this area.

Автор: Virginia Dressler
Название: Framing Privacy in Digital Collections with Ethical Decision Making
ISBN: 168173401X ISBN-13(EAN): 9781681734019
Издательство: Mare Nostrum (Eurospan)
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Цена: 46200.00 T
Наличие на складе: Невозможна поставка.
Описание: As digital collections continue to grow, the underlying technologies to serve up content also continue to expand and develop. As such, new challenges are presented whichcontinue to test ethical ideologies in everyday environs of the practitioner. There are currently no solid guidelines or overarching codes of ethics to address such issues. The digitization of modern archival collections, in particular, presents interesting conundrums when factors of privacy are weighed and reviewed in both small and mass digitization initiatives. Ethical decision making needs to be present at the onset of project planning in digital projects of all sizes, and we also need to identify the role and responsibility of the practitioner to make more virtuous decisions on behalf of those with no voice or awareness of potential privacy breaches.In this book, notions of what constitutes private information are discussed, as is the potential presence of such information in both analog and digital collections. This book lays groundwork to introduce the topic of privacy within digital collections by providing some examples from documented real-world scenarios and making recommendations for future research.A discussion of the notion privacy as concept will be included, as well as some historical perspective (with perhaps one the most cited work on this topic, for example, Warren and Brandeis' ""Right to Privacy,"" 1890). Concepts from the The Right to Be Forgotten case in 2014 (Google Spain SL, Google Inc. v Agencia Española de Protección de Datos, Mario Costeja González) are discussed as to how some lessons may be drawn from the response in Europe and also how European data privacy laws have been applied. The European ideologies are contrasted with the Right to Free Speech in the First Amendment in the U.S., highlighting the complexities in setting guidelines and practices revolving around privacy issues when applied to real life scenarios. Two ethical theories are explored: Consequentialism and Deontological. Finally, ethical decision making models will also be applied to our framework of digital collections. Three case studies are presented to illustrate how privacy can be defined within digital collections in some real-world examples.

Автор: Virginia Dressler
Название: Framing Privacy in Digital Collections with Ethical Decision Making
ISBN: 1681734036 ISBN-13(EAN): 9781681734033
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 66530.00 T
Наличие на складе: Невозможна поставка.
Описание: As digital collections continue to grow, the underlying technologies to serve up content also continue to expand and develop. As such, new challenges are presented whichcontinue to test ethical ideologies in everyday environs of the practitioner. There are currently no solid guidelines or overarching codes of ethics to address such issues. The digitization of modern archival collections, in particular, presents interesting conundrums when factors of privacy are weighed and reviewed in both small and mass digitization initiatives. Ethical decision making needs to be present at the onset of project planning in digital projects of all sizes, and we also need to identify the role and responsibility of the practitioner to make more virtuous decisions on behalf of those with no voice or awareness of potential privacy breaches.In this book, notions of what constitutes private information are discussed, as is the potential presence of such information in both analog and digital collections. This book lays groundwork to introduce the topic of privacy within digital collections by providing some examples from documented real-world scenarios and making recommendations for future research.A discussion of the notion privacy as concept will be included, as well as some historical perspective (with perhaps one the most cited work on this topic, for example, Warren and Brandeis' ""Right to Privacy,"" 1890). Concepts from the The Right to Be Forgotten case in 2014 (Google Spain SL, Google Inc. v Agencia Española de Protección de Datos, Mario Costeja González) are discussed as to how some lessons may be drawn from the response in Europe and also how European data privacy laws have been applied. The European ideologies are contrasted with the Right to Free Speech in the First Amendment in the U.S., highlighting the complexities in setting guidelines and practices revolving around privacy issues when applied to real life scenarios. Two ethical theories are explored: Consequentialism and Deontological. Finally, ethical decision making models will also be applied to our framework of digital collections. Three case studies are presented to illustrate how privacy can be defined within digital collections in some real-world examples.

Автор: Diane Rasmussen Pennington, Louise Spiteri
Название: Social Tagging in a Linked Data Environment
ISBN: 1783303395 ISBN-13(EAN): 9781783303397
Издательство: Facet
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Цена: 218240.00 T
Наличие на складе: Невозможна поставка.
Описание: This book, representing researchers and practitioners across different information professions, will explore how social tags can link content across a variety of environments.

Автор: Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis
Название: Data Exploration Using Example-Based Methods
ISBN: 1681734575 ISBN-13(EAN): 9781681734576
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 87780.00 T
Наличие на складе: Невозможна поставка.
Описание: Data usually comes in a plethora of formats and dimensions, rendering the information extraction and exploration processes challenging. Thus, being able to perform exploratory analyses of the data with the intent of having an immediate glimpse of some of the data properties is becoming crucial. Exploratory analyses should be simple enough to avoid complicated declarative languages (such as SQL) and mechanisms, while at the same time retaining the flexibility and expressiveness of such languages. Recently, we have witnessed a rediscovery of the so-called example-based methods, in which the user, or analyst, circumvents query languages by using examples as input. An example is a representative of the intended results or, in other words, an item from the result set. Example-based methods exploit inherent characteristics of the data to infer the results that the user has in mind but may not be able to (easily) express. They can be useful in cases where a user is looking for information in an unfamiliar dataset, when they are performing a particularly challenging task like finding duplicate items, or when they are simply exploring the data. In this book, we present an excursus over the main methods for exploratory analysis, with a particular focus on example-based methods. We show how different data types require different techniques and present algorithms that are specifically designed for relational, textual, and graph data. The book also presents the challenges and new frontiers of machine learning in online settings that have recently attracted the attention of the database community. The book concludes with a vision for further research and applications in this area.

Автор: Jeannette Ekstrom, Lorna Wildgaard
Название: Theories and Methods in Data Science Librarianship
ISBN: 178330409X ISBN-13(EAN): 9781783304097
Издательство: Bookpoint
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Цена: 137220.00 T
Наличие на складе: Невозможна поставка.
Описание: This book is a practical guide to how to get started as a data librarian with little time, no money but great enthusiasm. Theories and Methods in Data Science Librarianship describes and extends the role of the data science librarian through real-world cases and proposes several methods employed by public and academic libraries to develop and further educate the librarian. It is a collection of the best knowledge from published literature and experts in one place, creating an easy to read overview. The perspectives offered in the book are critical, in that they are reflexive about the role of the librarian and consider challenges and multidimensionality of the librarians profile. This multidimensionality requires theories that address data services as research objects (data-management, definition of concepts, researchers as individual agents, accessibility, funding, profile and education). The book covers: how to get started as a data librarian the history and the motivations of the data science librarianship community how data librarians can close the data literacy divide library policy and data science untangling the jungle of copyright and laws surrounding data use and data protection data ethics how library leaders can support and develop data science librarianship managing data science projects and services on no budget inspiring data science projects at the public library library carpentry skills and teaching how to identify user needs and develop relevant data science services. The book will be essential reading for librarians and information specialists working working with data related tasks including, research librarians, embedded librarians, metadata librarians, cataloguers, public librarians mediating the possibilities in data for library users and students of library and information science. It will also be of interest to those working in archives, museums and other cultural heritage institutions.

Автор: Jeannette Ekstrom, Lorna Wildgaard
Название: Theories and Methods in Data Science Librarianship
ISBN: 1783304081 ISBN-13(EAN): 9781783304080
Издательство: Bookpoint
Рейтинг:
Цена: 68580.00 T
Наличие на складе: Невозможна поставка.
Описание: This book is a practical guide to how to get started as a data librarian with little time, no money but great enthusiasm. Theories and Methods in Data Science Librarianship describes and extends the role of the data science librarian through real-world cases and proposes several methods employed by public and academic libraries to develop and further educate the librarian. It is a collection of the best knowledge from published literature and experts in one place, creating an easy to read overview. The perspectives offered in the book are critical, in that they are reflexive about the role of the librarian and consider challenges and multidimensionality of the librarians profile. This multidimensionality requires theories that address data services as research objects (data-management, definition of concepts, researchers as individual agents, accessibility, funding, profile and education). The book covers: how to get started as a data librarian the history and the motivations of the data science librarianship community how data librarians can close the data literacy divide library policy and data science untangling the jungle of copyright and laws surrounding data use and data protection data ethics how library leaders can support and develop data science librarianship managing data science projects and services on no budget inspiring data science projects at the public library library carpentry skills and teaching how to identify user needs and develop relevant data science services. The book will be essential reading for librarians and information specialists working working with data related tasks including, research librarians, embedded librarians, metadata librarians, cataloguers, public librarians mediating the possibilities in data for library users and students of library and information science. It will also be of interest to those working in archives, museums and other cultural heritage institutions.