Visual Information Retrieval Using Java and LIRE, Mathias Lux, Oge Marques

Автор: Harold Thimbleby, George Buchanan, Jennifer Pearso
Название: Designing for Digital Reading
ISBN: 1627052437 ISBN-13(EAN): 9781627052436
Издательство: Mare Nostrum (Eurospan)
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Цена: 41580.00 T
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Описание: Reading is a complex human activity that has evolved, and co-evolved, with technology over thousands of years. Mass printing in the fifteenth century firmly established what we know as the modern book, with its physical format of covers and paper pages, and now-standard features such as page numbers, footnotes, and diagrams. Today, electronic documents are enabling paperless reading supported by eReading technologies such as Kindles and Nooks, yet a high proportion of users still opt to print on paper before reading. This persistent habit of ""printing to read"" is one sign of the shortcomings of digital documents -- although the popularity of eReaders is one sign of the shortcomings of paper. How do we get the best of both worlds?The physical properties of paper (for example, it is light, thin, and flexible) contribute to the ease with which physical documents are manipulated; but these properties have a completely different set of affordances to their digital equivalents. Paper can be folded, ripped, or scribbled on almost subconsciously -- activities that require significant cognitive attention in their digital form, if they are even possible. The nearly subliminal interaction that comes from years of learned behavior with paper has been described as lightweight interaction, which is achieved when a person actively reads an article in a way that is so easy and unselfconscious that they are not apt to remember their actions later.Reading is now in a period of rapid change, and digital text is fast becoming the predominant mode of reading. As a society, we are merely at the start of the journey of designing truly effective tools for handling digital text.This book investigates the advantages of paper, how the affordances of paper can be realized in digital form, and what forms best support lightweight interaction for active reading. To understand how to design for the future, we review the ways reading technology and reader behavior have both changed and remained constant over hundreds of years. We explore the reasoning behind reader behavior and introduce and evaluate several user interface designs that implement these lightweight properties familiar from our everyday use of paper.We start by looking back, reviewing the development of reading technology and the progress of research on reading over many years. Drawing key concepts from this review, we move forward to develop and test methods for creating new and more effective interactions for supporting digital reading. Finally, we lay down a set of lightweight attributes which can be used as evidence-based guidelines to improve the usability of future digital reading technologies. By the end of this book, then, we hope you will be equipped to critique the present state of digital reading, and to better design and evaluate new interaction styles and technologies.

Автор: Manning, Christopher D. Raghavan, Prabhakar Schutz
Название: Introduction to information retrieval
ISBN: 0521865719 ISBN-13(EAN): 9780521865715
Издательство: Cambridge Academ
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Цена: 60190.00 T
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Описание: Class-tested and coherent, this textbook teaches information retrieval, including web search, text classification, and text clustering from basic concepts. Ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students. Slides and additional exercises are available for lecturers.

Автор: Joemon M Jose; Claudia Hauff; Ismail Sengor Alt?ng
Название: Advances in Information Retrieval
ISBN: 3319566075 ISBN-13(EAN): 9783319566078
Издательство: Springer
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Цена: 93160.00 T
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Описание: This book constitutes the refereed proceedings of the 39th European Conference on IR Research, ECIR 2017, held in Aberdeen, UK, in April 2017. Being the premier European forum for the presentation of new research results in the field of Information Retrieval, ECIR features a wide range of topics such as: IR Theory and Practice;

Автор: Michael S. Lew
Название: Principles of Visual Information Retrieval
ISBN: 1849968683 ISBN-13(EAN): 9781849968683
Издательство: Springer
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Цена: 153720.00 T
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Описание: This book is essential reading for researchers in VIR, and final-year undergraduate and postgraduate students on courses such as Multimedia Information Retrieval, Multimedia Databases, and others.

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
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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: 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)
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Цена: 87780.00 T
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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: Pavel Serdyukov; Pavel Braslavski; Sergei O. Kuzne
Название: Advances in Information Retrieval
ISBN: 3642369723 ISBN-13(EAN): 9783642369728
Издательство: Springer
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Цена: 111790.00 T
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Описание: This book constitutes the proceedings of the 35th European Conference on IR Research, ECIR 2013, held in Moscow, Russia, in March 2013. The 55 full papers, 38 poster papers and 10 demonstrations presented in this volume were carefully reviewed and selected from 287 submissions. IR theory and formal models; temporal IR, and microblog search.

Автор: Rao Shen, Marcos Andre Goncalves, Edward A. Fox
Название: Key Issues Regarding Digital Libraries: Evaluation and Integration
ISBN: 1608459128 ISBN-13(EAN): 9781608459124
Издательство: Mare Nostrum (Eurospan)
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Цена: 41580.00 T
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Описание: This is the second book based on the 5S (Societies, Scenarios, Spaces, Structures, Streams) approach to digital libraries (DLs). Leveraging the first volume on theoretical foundations, this title focuses on the key issues of evaluation and integration. These cross-cutting issues serve as a bridge for those interested in DLs.

Автор: Xiang Ren, Jiawei Han
Название: Mining Structures of Factual Knowledge from Text: An Effort-Light Approach
ISBN: 1681733927 ISBN-13(EAN): 9781681733920
Издательство: Mare Nostrum (Eurospan)
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Цена: 82230.00 T
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Описание: The real-world data, though massive, is largely unstructured, in the form of natural-language text. It is challenging but highly desirable to mine structures from massive text data, without extensive human annotation and labeling. In this book, we investigate the principles and methodologies of mining structures of factual knowledge (e.g., entities and their relationships) from massive, unstructured text corpora.Departing from many existing structure extraction methods that have heavy reliance on human annotated data for model training, our effort-light approach leverages human-curated facts stored in external knowledge bases as distant supervision and exploits rich data redundancy in large text corpora for context understanding. This effort-light mining approach leads to a series of new principles and powerful methodologies for structuring text corpora, including (1) entity recognition, typing and synonym discovery, (2) entity relation extraction, and (3) open-domain attribute-value mining and information extraction. This book introduces this new research frontier and points out some promising research directions.

Автор: Yunyao Li, Davood Rafiei
Название: Natural Language Data Management and Interfaces
ISBN: 1681734087 ISBN-13(EAN): 9781681734088
Издательство: Mare Nostrum (Eurospan)
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Цена: 66530.00 T
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Описание: The volume of natural language text data has been rapidly increasing over the past two decades, due to factors such as the growth of the Web, the low cost associated with publishing, and the progress on the digitization of printed texts. This growth combined with the proliferation of natural language systems for search and retrieving information provides tremendous opportunities for studying some of the areas where database systems and natural language processing systems overlap.This book explores two interrelated and important areas of overlap: (1) managing natural language data and (2) developing natural language interfaces to databases. It presents relevant concepts and research questions, state-of-the-art methods, related systems, and research opportunities and challenges covering both areas. Relevant topics discussed on natural language data management include data models, data sources, queries, storage and indexing, and transforming natural language text. Under natural language interfaces, it presents the anatomy of these interfaces to databases, the challenges related to query understanding and query translation, and relevant aspects of user interactions. Each of the challenges is covered in a systematic way: first starting with a quick overview of the topics, followed by a comprehensive view of recent techniques that have been proposed to address the challenge along with illustrative examples. It also reviews some notable systems in details in terms of how they address different challenges and their contributions. Finally, it discusses open challenges and opportunities for natural language management and interfaces.The goal of this book is to provide an introduction to the methods, problems, and solutions that are used in managing natural language data and building natural language interfaces to databases. It serves as a starting point for readers who are interested in pursuing additional work on these exciting topics in both academic and industrial environments.

Автор: Maarten de Rijke; Tom Kenter; Arjen P. de Vries; C
Название: Advances in Information Retrieval
ISBN: 3319060279 ISBN-13(EAN): 9783319060279
Издательство: Springer
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Цена: 116450.00 T
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Описание: This book constitutes the proceedings of the 36th European Conference on IR Research, ECIR 2014, held in Amsterdam, The Netherlands, in April 2014. The 33 full papers, 50 poster papers and 15 demonstrations presented in this volume were carefully reviewed and selected from 288 submissions.

Автор: Donald H. Kraft, Erin Colvin
Название: Fuzzy Information Retrieval
ISBN: 1627059520 ISBN-13(EAN): 9781627059527
Издательство: Mare Nostrum (Eurospan)
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Цена: 36030.00 T
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Описание: Information retrieval (IR) is often seen as a subfield of computer science and shares some modelling, applications, storage applications and techniques, as do other disciplines like artificial intelligence, database management, and parallel computing. This book introduces the topic of IR and how it differs from other computer science disciplines.