Introduction to Modern Information Retrieval, G. G. Chowdhury

Автор: Manning, Christopher D. Raghavan, Prabhakar Schutz
Название: Introduction to information retrieval
ISBN: 0521865719 ISBN-13(EAN): 9780521865715
Издательство: Cambridge Academ
Рейтинг:
Цена: 60190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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: Massimo Melucci
Название: Introduction to Information Retrieval and Quantum Mechanics
ISBN: 3662483122 ISBN-13(EAN): 9783662483121
Издательство: Springer
Рейтинг:
Цена: 79190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces the quantum mechanical framework to information retrieval scientists seeking a new perspective on foundational problems.

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)
Рейтинг:
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: Miroslav Kubat
Название: An Introduction to Machine Learning
ISBN: 3319348868 ISBN-13(EAN): 9783319348865
Издательство: Springer
Рейтинг:
Цена: 46570.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of interesting applications.

Автор: Harold Thimbleby, George Buchanan, Jennifer Pearso
Название: Designing for Digital Reading
ISBN: 1627052437 ISBN-13(EAN): 9781627052436
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 41580.00 T
Наличие на складе: Нет в наличии.
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: 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)
Рейтинг:
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: Nigel Ford
Название: Introduction to Information Behaviour
ISBN: 1783302879 ISBN-13(EAN): 9781783302871
Издательство: Facet
Рейтинг:
Цена: 168960.00 T
Наличие на складе: Невозможна поставка.
Описание: This landmark textbook is an essential primer for students and practitioners interested in information seeking, needs and behaviour, user studies and information literacy.