Human Vision & Language Systems Books

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Programming Collective Intelligence: Building Smart Web 2.0 Applications

Toby Segaran

Programming Collective Intelligence: Building Smart Web 2.0 Applications Toby Segaran Amazon Price: $26.39
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Customer Reviews:
Total reviews: 37 Average rating: 4.5 of 5

Editorial Review:

Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains: Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in adataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details." -- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths." -- Tim Wolters, CTO, Collective Intellect

Pattern Recognition and Machine Learning (Information Science and Statistics)

Christopher M. Bishop

Pattern Recognition and Machine Learning (Information Science and Statistics) Christopher M. Bishop Amazon Price: $67.96
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Total reviews: 41 Average rating: 4.0 of 5

Editorial Review:

The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the underlying algorithms and techniques. For example, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic techniques. The practical applicability of Bayesian methods has been greatly enhanced by the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation, while new models based on kernels have had a significant impact on both algorithms and applications.

This completely new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

The book is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. Extensive support is provided for course instructors, including more than 400 exercises, graded according to difficulty. Example solutions for a subset of the exercises are available from the book web site, while solutions for the remainder can be obtained by instructors from the publisher. The book is supported by a great deal of additional material, and the reader is encouraged to visit the book web site for the latest information.

Coming soon:

*For students, worked solutions to a subset of exercises available on a public web site (for exercises marked "www" in the text)

*For instructors, worked solutions to remaining exercises from the Springer web site

*Lecture slides to accompany each chapter

*Data sets available for download

Speech and Language Processing (2nd Edition) (Prentice Hall Series in Artificial Intelligence)

Daniel Jurafsky, James H. Martin

Speech and Language Processing (2nd Edition) (Prentice Hall Series in Artificial Intelligence) Daniel Jurafsky, James H. Martin Amazon Price: $94.40
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Subjects -> Computers & Internet -> Software -> Business -> Speech Processing
Subjects -> Computers & Internet -> Software -> Voice Recognition

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Total reviews: 20 Average rating: 4.5 of 5

Editorial Review:

An explosion of Web-based language techniques, merging of distinct fields, availability of phone-based dialogue systems, and much more make this an exciting time in speech and language processing. The first of its kind to thoroughly cover language technology – at all levels and with all modern technologies – this book takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. Builds each chapter around one or more worked examples demonstrating the main idea of the chapter, usingthe examples to illustrate the relative strengths and weaknesses of various approaches. Adds coverage of statistical sequence labeling, information extraction, question answering and summarization, advanced topics in speech recognition, speech synthesis. Revises coverage of language modeling, formal grammars, statistical parsing, machine translation, and dialog processing. A useful reference for professionals in any of the areas of speech and language processing.

Text Mining Application Programming (Programming Series)

Manu Konchady

Text Mining Application Programming (Programming Series) Manu Konchady Amazon Price: $37.77
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Total reviews: 5 Average rating: 5.0 of 5

Editorial Review:

Text Mining Application Programming teaches software developers how to mine the vast amounts of information available on the Web, internal networks, and desktop files and turn it into usable data. The book helps developers understand the problems associated with managing unstructured text, and explains how to build your own mining tools using standard statistical methods from information theory, artificial intelligence, and operations research. Each of the topics covered are thoroughly explained and then a practical implementation is provided. The book begins with a brief overview of text data, where it can be found, and the typical search engines and tools used to search and gather this text. It details how to build tools for extracting and using the text, and covers the mathematics behind many of the algorithms used in building these tools. From there you'll learn how to build tokens from text, construct indexes, and detect patterns in text. You'll also find methods to extract the names of people, places, and organizations from an email, a news article, or a Web page. The next portion of the book teaches you how to find information on the Web, the structure of the Web, and how to build spiders to crawl the Web. Text categorization is also described in the context of managing email. The final part of the book covers information monitoring, summarization, and a simple Question & Answer (Q&A) system. The code used in the book is written in Perl, but knowledge of Perl is not necessary to run the software. Developers with an intermediate level of experience with Perl can customize the software. Although the book is about programming, methods are explained with English-like pseudocode and the source code is provided on the CD-ROM. After reading this book, you'll be ready to tap into the bevy of information available online in ways you never thought possible.

Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications)

Bing Liu

Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications) Bing Liu Amazon Price: $47.96
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Total reviews: 1 Average rating: 5.0 of 5

Editorial Review:

Web mining aims to discover useful information and knowledge from the Web hyperlink structure, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semistructured and unstructured nature of the Web data and its heterogeneity. It has also developed many of its own algorithms and techniques.

Liu has written a comprehensive text on Web data mining. Key topics of structure mining, content mining, and usage mining are covered both in breadth and in depth. His book brings together all the essential concepts and algorithms from related areas such as data mining, machine learning, and text processing to form an authoritative and coherent text.

The book offers a rich blend of theory and practice, addressing seminal research ideas, as well as examining the technology from a practical point of view. It is suitable for students, researchers and practitioners interested in Web mining both as a learning text and a reference book. Lecturers can readily use it for classes on data mining, Web mining, and Web search. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.

Mastering Algorithms with C (Mastering)

Kyle Loudon

Mastering Algorithms with C (Mastering) Kyle Loudon Amazon Price: $29.16
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Subjects -> Computers & Internet -> Microsoft -> Development -> C & C++ Windows Programming
Subjects -> Computers & Internet -> Programming -> Algorithms -> General

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Total reviews: 15 Average rating: 3.5 of 5

Editorial Review:

Written with the intermediate to advanced C programmer in mind, Mastering Algorithms with C delivers a no-nonsense guide to the most common algorithms needed by real-world developers.

The highlight of the book has to be its concise and readable C functions for all the algorithms presented here, including basics like linked lists, stacks to trees, graphs, and sorting/searching algorithms. The C functions that implement these algorithms are clearly printed and remarkably easy to read. You can use this sample code directly or adapt it into your C/C++ code.

Although mathematical concepts like Big-O notation are discussed, the authors don't get bogged down in the computer science theory surrounding algorithms. Instead, they present the most tried-and-true algorithms available today in an efficient format. Besides introducing each algorithm, they describe how each is used in computing today, along with a short demo application. Some of these samples are quite low-level, such as a virtual memory manager implemented with linked lists. Most examples are more of general interest, such as a graphing example that counts network hops.

Each section ends with questions and answers about how the algorithms work, along with references to other algorithms (both in the book and from other sources). The authors concentrate on the most useful algorithms available today and don't try to cover every available variation. Busy readers will appreciate the intelligent selection--and efficient presentation--used here.

There are a number of books on C algorithms, but Master Algorithms with C is one of the most concise and immediately useful. It's a perfect choice for the working C/C++ programmer who's in a hurry to find just the right algorithm for writing real-world code. --Richard Dragan

Topics covered: Algorithm efficiency, pointer basics, arrays, recursion, Big-O Notation, linked lists, stacks, queues, sets, hash tables, trees and B-trees, searching, heaps and priority queues, graphs, sorting and searching algorithms, numerical methods, data compression, Huffman coding, LZ77, data encryption, DES, RSA, graph algorithms, minimum spanning trees, geometric algorithms, and convex hulls.

Human-Machine Reconfigurations: Plans and Situated Actions (Learning in Doing: Social, Cognitive and Computational Perspectives)

Lucy Suchman

Human-Machine Reconfigurations: Plans and Situated Actions (Learning in Doing: Social, Cognitive and Computational Perspectives) Lucy Suchman Amazon Price: $28.79
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Editorial Review:

This book considers how agencies are currently figured at the human-machine interface, and how they might be imaginatively and materially reconfigured. Contrary to the apparent enlivening of objects promised by the sciences of the artificial, the author proposes that the rhetorics and practices of those sciences work to obscure the performative nature of both persons and things. The question then shifts from debates over the status of human-like machines, to that of how humans and machines are enacted as similar or different in practice, and with what theoretical, practical and political consequences. Drawing on recent scholarship across the social sciences, humanities and computing, the author argues for research aimed at tracing the differences within specific sociomaterial arrangements without resorting to essentialist divides. This requires expanding our unit of analysis, while recognizing the inevitable cuts or boundaries through which technological systems are constituted.

Semantic Digital Libraries

Semantic Digital Libraries Amazon Price: $74.24
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Subjects -> Computers & Internet -> Computer Science -> Artificial Intelligence -> General AAS

Editorial Review:

Libraries have always been an inspiration for the standards and technologies developed by semantic web activities. However, except for the Dublin Core specification, semantic web and social networking technologies have not been widely adopted and further developed by major digital library initiatives and projects. Yet semantic technologies offer a new level of flexibility, interoperability, and relationships for digital repositories.

Kruk and McDaniel present semantic web-related aspects of current digital library activities, and introduce their functionality; they show examples ranging from general architectural descriptions to detailed usages of specific ontologies, and thus stimulate the awareness of researchers, engineers, and potential users of those technologies. Their presentation is completed by chapters on existing prototype systems such as JeromeDL, BRICKS, and Greenstone, as well as a look into the possible future of semantic digital libraries.

This book is aimed at researchers and graduate students in areas like digital libraries, the semantic web, social networks, and information retrieval. This audience will benefit from detailed descriptions of both today’s possibilities and also the shortcomings of applying semantic web technologies to large digital repositories of often unstructured data.

Model Driven Architecture and Ontology Development

Dragan Gasevic, Dragan Djuric, Vladan Devedzic

Model Driven Architecture and Ontology Development Dragan Gasevic, Dragan Djuric, Vladan Devedzic Amazon Price: $47.96
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Total reviews: 1 Average rating: 5.0 of 5

Editorial Review:

Defining a formal domain ontology is generally considered a useful, not to say necessary step in almost every software project. This is because software deals with ideas rather than with self-evident physical artefacts. However, this development step is hardly ever done, as ontologies rely on well-defined and semantically powerful AI concepts such as description logics or rule-based systems, and most software engineers are largely unfamiliar with these.

Gaševic and his co-authors try to fill this gap by covering the subject of MDA application for ontology development on the Semantic Web. Part I of their book describes existing technologies, tools, and standards like XML, RDF, OWL, MDA, and UML. Part II presents the first detailed description of OMG’s new ODM (Ontology Definition Metamodel) initiative, a specification which is expected to be in the form of an OMG language like UML. Finally, Part III is dedicated to applications and practical aspects of developing ontologies using MDA-based languages. The book is supported by a website showing many ontologies, UML and other MDA-based models, and the transformations between them.

"The book is equally suited to those who merely want to be informed of the relevant technological landscape, to practitioners dealing with concrete problems, and to researchers seeking pointers to potentially fruitful areas of research. The writing is technical yet clear and accessible, illustrated throughout with useful and easily digestible examples." from the Foreword by Bran Selic, IBM Rational Software, Canada.

"I do not know another book that offers such a high quality insight into UML and ontologies." Steffen Staab, U Koblenz, Germany

AI Application Programming (Programming Series) (Programming Series)

M. Tim Jones

AI Application Programming (Programming Series) (Programming Series) M. Tim Jones Amazon Price: $37.77
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Total reviews: 18 Average rating: 4.5 of 5

Editorial Review:

The popularity of artificial intelligence continues to grow as more and more uses are found for the technology. AI Application Programming Second Edition is completely updated to supply both the conceptual background and the real-world examples needed to begin using AI in software projects. Each technology is illustrated with a model implementation and application, and complete source code for each example is provided on the companion CD-ROM. Selected applications cover data mining, genetic algorithms, game programming, embedded rules-based engines, and the World Wide Web.

KEY FEATURES:
* Covers cutting-edge AI concepts such as neural networks, natural language processing, intelligent agents, genetic algorithms, rule-based systems, unsupervised learning algorithms, migratory software, and more
* Teaches each AI concept through a practical application, including a financial data miner, a Web spider, a networked data collector, a game program, an embedded battery charger control system, an embedded rules-based engine for log monitoring, and a fault tolerance subsystem
* Groups AI topics by conceptual subfields (machine learning, evolutionary methods, symbolic methods) for better "big picture" understanding and more focused specialization
* Provides a background in the history of AI, the distinct branches of this broad field, and the philosophical underpinnings and issues associated with these technologies
* Includes a CD-ROM (Win/Linux) with complete, fully commented source code in C for every application in the book
* Exercise sets for each chapter are located in Appendix A for use as a Textbook


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