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ALGORITHMS OF THE INTELLIGENT WEB

Author: Haralambos Marmanis
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Special Features: Learning Elements:· How to create recommendations just like those on Netflix and Amazon· How to implement Google's Pagerank algorithm· How to discover matches on social-networking sites· How to organize the discussions on your favorite news group· How to select topics of interest from shared bookmarks· How to leverage user clicks· How to categorize emails based on their content· How to build applications that do targeted advertising· How to implement fraud detection About The Book: Algorithms of the Intelligent Web is an example-driven blueprint for creating applications that collect, analyze, and act on the massive quantities of data users leave in their wake as they use the web. You'll learn how to build Amazon- and Netflix-style recommendation engines, and how the same techniques apply to people matches on social-networking sites. See how click-trace analysis can result in smarter ad rotations. With a plethora of examples and extensive detail, this book shows you how to build Web 2.0 applications that are as smart as your users.


Algorithms of the Intelligent Web

Author: Douglas G McIlwraith
Publisher: Manning Publications
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Summary Algorithms of the Intelligent Web, Second Edition teaches the most important approaches to algorithmic web data analysis, enabling you to create your own machine learning applications that crunch, munge, and wrangle data collected from users, web applications, sensors and website logs. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Valuable insights are buried in the tracks web users leave as they navigate pages and applications. You can uncover them by using intelligent algorithms like the ones that have earned Facebook, Google, and Twitter a place among the giants of web data pattern extraction. About the Book Algorithms of the Intelligent Web, Second Edition teaches you how to create machine learning applications that crunch and wrangle data collected from users, web applications, and website logs. In this totally revised edition, you'll look at intelligent algorithms that extract real value from data. Key machine learning concepts are explained with code examples in Python's scikit-learn. This book guides you through algorithms to capture, store, and structure data streams coming from the web. You'll explore recommendation engines and dive into classification via statistical algorithms, neural networks, and deep learning. What's Inside Introduction to machine learning Extracting structure from data Deep learning and neural networks How recommendation engines work About the Reader Knowledge of Python is assumed. About the Authors Douglas McIlwraith is a machine learning expert and data science practitioner in the field of online advertising. Dr. Haralambos Marmanis is a pioneer in the adoption of machine learning techniques for industrial solutions. Dmitry Babenko designs applications for banking, insurance, and supply-chain management. Foreword by Yike Guo. Table of Contents Building applications for the intelligent web Extracting structure from data: clustering and transforming your data Recommending relevant content Classification: placing things where they belong Case study: click prediction for online advertising Deep learning and neural networks Making the right choice The future of the intelligent web Appendix - Capturing data on the web


The Intelligent Web

Author: Gautam Shroff
Publisher: Oxford University Press
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Early hopes for Artificial Intelligence soon evaporated. But, driven by the need for smarter searching and advert placing, increasingly sophisticated algorithms, combined with the sheer amount of data on the Web, have led to a growing "Web intelligence". Gautam Shroff explores this trend, its conceptual basis, and what the future may hold.


Intelligent Information Processing and Web Mining

Author: Mieczyslaw A. Klopotek
Publisher: Springer Science & Business Media
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The international conference Intelligent Information Processing and Web Mining IIS:IIPWM’05, organized in Gda?sk-Sobieszewo on 13–16th June, 2005, was a continuation of a long tradition of conferences on applications of Arti?cial Intelligence (AI) in Information Systems (IS), organized by the Institute of Computer Science of Polish Academy of Sciences in cooperation with other scienti?c and business institutions. The Institute itself is deeply engaged in research both in AI and IS and many scientists view it as a leading institution both in fundamental and - plied research in these areas in Poland. The originators of this conference series, Prof. M. D?browski and Dr. M. Michalewicz had in 1992 a long-term goal of bringing together scientists and industry of di?erent braches from Poland and abroad to achieve a creative synthesis. One can say that their dream has come to reality. Scientists from ?ve continents made their subm- sions to this conference. A brief look at the a?liations makes international cooperation visible. The research papers have either a motivation in c- crete applications or are o?-springs of some practical requests. This volume presents the best papers carefully chosen from a large set of submissions (about 45%). At this point we would like to express our thanks to the m- bers of Programme Committee for their excellent job. Also we are thankful to the organizers of the special sessions accompanying this conference: Jan Komorowski, Adam Przepiórkowski, Zbigniew W.


Building an Intelligent Web Theory and Practice

Author: Pawan Lingras
Publisher: Jones & Bartlett Publishers
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The World Wide Web has become an extremely popular way of publishing and distributing electronic resources. Though the Web is rich with information, collecting and making sense of this data is difficult because it is rather unorganized. Building an Intelligent Web introduces students and professionals to the state-of-the art development of Web Intelligence techniques and teaches how to apply these techniques to develop the next generation of intelligent Web sites. Each chapter contains theoretical bases, which are also illustrated with the help of simple numeric examples, followed by practical implementation. Students will find Building an Intelligent Web to be an active and exciting introduction to advanced Web mining topics. Topics covered include Web Intelligence, Information Retrieval, Semantic Web, Classification and Association Rules, SQL, Database Theory, Applications to e-commerce and Bioinformatics, Clustering, Modeling Web Topology, and much more!


Advances in Intelligent Web Mastering

Author: Katarzyna M. Wegrzyn-Wolska
Publisher: Springer Science & Business Media
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This book contains papers presented at the 5th Atlantic Web Intelligence Conference, AWIC’2007, held in Fontainbleau, France, in June 2007, and organized by Esigetel, Technical University of Lodz, and Polish Academy of Sciences. It includes reports from the front of diverse fields of the Web, including application of artificial intelligence, design, information retrieval and interpretation, user profiling, security, and engineering.


Evolution of the Web in Artificial Intelligence Environments

Author: Richi Nayak
Publisher: Springer Science & Business Media
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The Web has revolutionized the way we seek information on all aspects of education, entertainment, business, health and so on. The Web has evolved into a publishing medium, global electronic market and increasingly, a platform for conducting electronic commerce. A part of this success can be attributed to the tremendous advances made in the Artificial Intelligence field. The popularity of the Web has opened many opportunities to develop smart Web-based systems using artificial intelligence techniques. There exist numerous Web technology and applications that can benefit with the application of artificial intelligence techniques. It is not possible to cover them all in one book with a required degree of quality, depth and width. We present this book to discuss some important Web developments by using artificial intelligence techniques in the areas of Web personalisation, semantic Web and Web services. The primary readers of this book are undergraduate/postgraduate students, researchers and practitioners in information technology and computer science related areas. The success of this book is largely due to the collective efforts of a great team consisting of authors and reviewers. We are grateful to them for their vision and wonderful support. The final quality of selected papers reflects their efforts. Finally we would like to thank the Queensland University of Technology, Brisbane Australia and University of South Australia, Adelaide Australia for providing us the resources and time to undertake this task. We extend our sincere thanks to Scientific Publishing Services Pvt. Ltd., for the editorial support.


Intelligent Exploration of the Web

Author: Piotr S. Szczepaniak
Publisher: Springer Science & Business Media
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The Web is the nervous system of information society. As such, it has a pervasive influence on our daily lives. And yet, in some ways the Web does not have a high MIQ (Machine IQ). What can be done to enhance it? This is the leitmotif of "Intelligent Exploration of the Web," (lEW)--a collection of articles co-edited by Drs. Szczepaniak, Segovia, Kacprzyk and, to a small degree, myself. The articles that comprise lEW address many basic problems ranging from structure analysis of Internet documents and Web dialogue management to intelligent Web agents for extraction of information, and bootstrapping an ontology-based information extraction system. Among the basic problems, one that stands out in importance is the problem of search. Existing search engines have many remarkable capabilities. But what is not among them is the deduction capability--the capability to answer a query by drawing on information which resides in various parts of the knowledge base. An example of a query might be "How many Ph.D. degrees in computer science were granted by European universities in 1996?" No existing search engine is capable of dealing with queries of comparable or even much lower complexity. Basically, what we would like to do is to add deduction capability to a search engine, with the aim of transforming it into a question-answering system, or a QI A system, for short. This is a problem that is of major importance and a challenge that is hard to meet.


Artificial Intelligence Illuminated

Author: Ben Coppin
Publisher: Jones & Bartlett Learning
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Artificial Intelligence Illuminated presents an overview of the background and history of artificial intelligence, emphasizing its importance in today's society and potential for the future. The book covers a range of AI techniques, algorithms, and methodologies, including game playing, intelligent agents, machine learning, genetic algorithms, and Artificial Life. Material is presented in a lively and accessible manner and the author focuses on explaining how AI techniques relate to and are derived from natural systems, such as the human brain and evolution, and explaining how the artificial equivalents are used in the real world. Each chapter includes student exercises and review questions, and a detailed glossary at the end of the book defines important terms and concepts highlighted throughout the text.


Research Handbook on the Law of Artificial Intelligence

Author: Woodrow Barfield
Publisher: Edward Elgar Publishing
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The field of artificial intelligence (AI) has made tremendous advances in the last two decades, but as smart as AI is now, it is getting smarter and becoming more autonomous. This raises a host of challenges to current legal doctrine, including whether AI/algorithms should count as ‘speech’, whether AI should be regulated under antitrust and criminal law statutes, and whether AI should be considered as an agent under agency law or be held responsible for injuries under tort law. This book contains chapters from US and international law scholars on the role of law in an age of increasingly smart AI, addressing these and other issues that are critical to the evolution of the field.