Download or read book Information Retrieval Technology written by Buren Zheng and published by Springer Science & Business Media. This book was released on 2010-11-16 with total page 642 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th Asia Information Retrieval Symposium, AIRS 2010, held in Taipei, Taiwan, in December 2010. The 26 revised full papers and 31 revised poster papers presented were carefully reviewed and selected from 120 submissions. All current aspects of information retrieval - in theory and practice - are addressed; the papers are organized in topical sections on information retrieval models, machine learning for information retrieval, user studies and evaluation, natural language processing for information retrieval, Web and question answering, and multimedia.
Download or read book Developments in Language Theory written by Yuan Gao and published by Springer Science & Business Media. This book was released on 2010-07-30 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 14th International Conference on Developments in Language Theory, DLT 2010, held in London, Ontario, Canada, in August 2010. The 32 regular papers presented were carefully reviewed and selected from numerous submissions. The volume also contains the papers or abstracts of 6 invited speakers, as well as a 2-page abstract for each of the 6 poster papers. The topics addressed are formal languages, automata theory, computability, complexity, logic, petri nets and related areas.
Download or read book Advances in Information Retrieval written by Joemon M. Jose and published by Springer Nature. This book was released on 2020-04-11 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 12035 and 12036 constitutes the refereed proceedings of the 42nd European Conference on IR Research, ECIR 2020, held in Lisbon, Portugal, in April 2020.* The 55 full papers presented together with 8 reproducibility papers, 46 short papers, 10 demonstration papers, 12 invited CLEF papers, 7 doctoral consortium papers, 4 workshop papers, and 3 tutorials were carefully reviewed and selected from 457 submissions. They were organized in topical sections named: Part I: deep learning I; entities; evaluation; recommendation; information extraction; deep learning II; retrieval; multimedia; deep learning III; queries; IR – general; question answering, prediction, and bias; and deep learning IV. Part II: reproducibility papers; short papers; demonstration papers; CLEF organizers lab track; doctoral consortium papers; workshops; and tutorials. *Due to the COVID-19 pandemic, this conference was held virtually.
Download or read book Advances in Information Retrieval written by Allan Hanbury and published by Springer. This book was released on 2015-03-16 with total page 882 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 37th European Conference on IR Research, ECIR 2015, held in Vienna, Austria, in March/April 2015. The 44 full papers, 41 poster papers and 7 demonstrations presented together with 3 keynotes in this volume were carefully reviewed and selected from 305 submissions. The focus of the papers were on following topics: aggregated search and diversity, classification, cross-lingual and discourse, efficiency, evaluation, event mining and summarisation, information extraction, recommender systems, semantic and graph-based models, sentiment and opinion, social media, specific search tasks, temporal models and features, topic and document models, user behavior and reproducible IR.
Download or read book Java Data Science Made Easy written by Richard M. Reese and published by Packt Publishing Ltd. This book was released on 2017-07-07 with total page 715 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data collection, processing, analysis, and more About This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples A highly practical course covering a broad set of topics - from the basics of Machine Learning to Deep Learning and Big Data frameworks. Who This Book Is For This course is meant for Java developers who are comfortable developing applications in Java, and now want to enter the world of data science or wish to build intelligent applications. Aspiring data scientists with some understanding of the Java programming language will also find this book to be very helpful. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing your existing Java stack, this book is for you! What You Will Learn Understand the key concepts of data science Explore the data science ecosystem available in Java Work with the Java APIs and techniques used to perform efficient data analysis Find out how to approach different machine learning problems with Java Process unstructured information such as natural language text or images, and create your own search Learn how to build deep neural networks with DeepLearning4j Build data science applications that scale and process large amounts of data Deploy data science models to production and evaluate their performance In Detail Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this course, we cover the basic as well as advanced data science concepts and how they are implemented using the popular Java tools and libraries.The course starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. You will examine the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation. Throughout this course, the chapters will illustrate a challenging data science problem, and then go on to present a comprehensive, Java-based solution to tackle that problem. You will cover a wide range of topics – from classification and regression, to dimensionality reduction and clustering, deep learning and working with Big Data. Finally, you will see the different ways to deploy the model and evaluate it in production settings. By the end of this course, you will be up and running with various facets of data science using Java, in no time at all. This course contains premium content from two of our recently published popular titles: Java for Data Science Mastering Java for Data Science Style and approach This course follows a tutorial approach, providing examples of each of the concepts covered. With a step-by-step instructional style, this book covers various facets of data science and will get you up and running quickly.
Download or read book Computer Science Logic written by Jacques Duparc and published by Springer. This book was released on 2007-08-24 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 21st International Workshop on Computer Science Logic, CSL 2007, held as the 16th Annual Conference of the EACSL in Lausanne, Switzerland. The 36 revised full papers presented together with the abstracts of six invited lectures are organized in topical sections on logic and games, expressiveness, games and trees, logic and deduction, lambda calculus, finite model theory, linear logic, proof theory, and game semantics.
Download or read book Mastering Java for Data Science written by Alexey Grigorev and published by Packt Publishing Ltd. This book was released on 2017-04-27 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Java to create a diverse range of Data Science applications and bring Data Science into production About This Book An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine. Who This Book Is For This book is intended for software engineers who are comfortable with developing Java applications and are familiar with the basic concepts of data science. Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing the existing stack, this book is for you! What You Will Learn Get a solid understanding of the data processing toolbox available in Java Explore the data science ecosystem available in Java Find out how to approach different machine learning problems with Java Process unstructured information such as natural language text or images Create your own search engine Get state-of-the-art performance with XGBoost Learn how to build deep neural networks with DeepLearning4j Build applications that scale and process large amounts of data Deploy data science models to production and evaluate their performance In Detail Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings. Style and approach This is a practical guide where all the important concepts such as classification, regression, and dimensionality reduction are explained with the help of examples.
Download or read book Ranked Set Sampling Models and Methods written by Bouza-Herrera, Carlos N. and published by IGI Global. This book was released on 2021-08-06 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: When it comes to data collection and analysis, ranked set sampling (RSS) continues to increasingly be the focus of methodological research. This type of sampling is an alternative to simple random sampling and can offer substantial improvements in precision and efficient estimation. There are different methods within RSS that can be further explored and discussed. On top of being efficient, RSS is cost-efficient and can be used in situations where sample units are difficult to obtain. With new results in modeling and applications, and a growing importance in theory and practice, it is essential for modeling to be further explored and developed through research. Ranked Set Sampling Models and Methods presents an innovative look at modeling survey sampling research and new models of RSS along with the future potentials of it. The book provides a panoramic view of the state of the art of RSS by presenting some previously known and new models. The chapters illustrate how the modeling is to be developed and how they improve the efficiency of the inferences. The chapters highlight topics such as bootstrap methods, fuzzy weight ranked set sampling method, item count technique, stratified ranked set sampling, and more. This book is essential for statisticians, social and natural science scientists, physicians and all the persons involved with the use of sampling theory in their research along with practitioners, researchers, academicians, and students interested in the latest models and methods for ranked set sampling.
Download or read book The Routledge Handbook of Soft Power written by Naren Chitty and published by Taylor & Francis. This book was released on 2023-07-07 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Routledge Handbook of Soft Power (2nd Edition) offers a comprehensive, detailed, and ground-breaking examination of soft power – a key factor in cultural diplomacy, cultural relations, and public diplomacy. Interrogating soft power as influence, the handbook examines manifestations in media, public mind, policy, and theory – in a fraught geopolitical climate, one demanding reconceptualization of soft power’s role in state and civic society behaviour. Part I provides important new conceptualization and critical analysis of soft power from international relations, philosophical, and other social theoretical perspectives; analyses multiple methods of soft power measurement and makes proposals; and connects soft power innovatively with other concepts Part II addresses soft power and contemporary issues by examining new technology and soft power intentions, soft power and states’ performance during the global pandemic, and soft power and values Part III investigates cases from China, France, Greece, Israel, Japan, Kazhakstan, Poland, Russia, South Korea, Spain, Türkiye, and the United States – some in combination. This innovative handbook is a definitive resource for inquirers into soft power desiring to familiarize themselves with cutting-edge debates and research. It will be of interest and value to students, researchers, and policy makers working in cultural relations, international communication, international relations, public diplomacy, and contiguous fields.
Download or read book Advances in Information Retrieval written by Nazli Goharian and published by Springer Nature. This book was released on with total page 529 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Knowledge Exploration in Life Science Informatics written by Jesús A. López and published by Springer. This book was released on 2005-01-27 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of the Springer Lecture Notes in Computer Science series contains the contributions presented at the International Symposium on Knowledge Exploration in Life Science Informatics (KELSI 2004) held in Milan, Italy, 25-26 November 2004. The two main objectives of the symposium were: • To explore the symbiosis between information and knowledge technologies and v- ious life science disciplines, such as biochemistry, biology, neuroscience, medical research, social sciences, and so on. • To investigate the synergy among different life science informatics areas, including cheminformatics,bioinformatics,neuroinformatics,medical informatics,systems - ology, socionics, and others. Modern life sciences investigate phenomena and systems at the level of molecules, cells, tissues, organisms, and populations. Typical areas of interest include natural e- lution, development,disease, behavior,cognition,and consciousness.This quest is g- eratinganoverwhelmingandfast-growingamountofdata,information,andknowledge, re?ecting living systems at different levels of organization. Future progress of the life sciences will depend on effective and ef?cient management, sharing, and exploitation of these resources by computational means.
Download or read book OTS written by United States. Department of Commerce. Office of Technical Services and published by . This book was released on 1975 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Database Systems for Advanced Applications written by Jeffrey Xu Yu and published by Springer Science & Business Media. This book was released on 2011-04-06 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two volume set LNCS 6587 and LNCS 6588 constitutes the refereed proceedings of the 16th International Conference on Database Systems for Advanced Applications, DASFAA 2011, held in Saarbrücken, Germany, in April 2010. The 53 revised full papers and 12 revised short papers presented together with 2 invited keynote papers, 22 demonstration papers, 4 industrial papers, 8 demo papers, and the abstract of 1 panel discussion, were carefully reviewed and selected from a total of 225 submissions. The topics covered are social network, social network and privacy, data mining, probability and uncertainty, stream processing, graph, XML, XML and graph, similarity, searching and digital preservation, spatial queries, query processing, as well as indexing and high performance.
Download or read book Information Retrieval written by Pavel Braslavski and published by Springer. This book was released on 2015-12-09 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 8th Russian Summer School on Information Retrieval, RuSSIR 2014, held in Nizhniy Novgorod, Russia, in August 2014. The volume includes 6 tutorial papers, summarizing lectures given at the event, and 8 revised papers from the school participants.The papers focus on various aspects of information retrieval.
Download or read book Pedology written by R. Duchaufour and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first of two volumes intended to replace the old and now out of print Precis de pedologie, the previous three editions of which were pro duced by the same publisher in 1960, 1965 and 1970. It was apparent that the term 'precis', which means that the text was neces sarily condensed and summarised, no longer corresponded with the present day situation, for pedology has developed considerably in the past 10 years and it now makes use of the most modern and varied research techniques. It has become an entirely separate discipline and has assumed, at least in certain countries, considerable importance. In addition, different schools of thought have developed and their sometimes contradictory viewpoints are presented at many international conferences, which, if valid conclusions are to be reached from them, required considerable space for discussion. Thus, even by being very concise it was no longer possible to deal with the whole of soil science within the space of one volume, so that a two volume format became a necessity. As soil science is known to have two fundamentally distinct aspects, it has been easy to determine the contents of each volume and also to give each an identity and unity, as well as enabling a different kind of presentation to be made in each case.
Download or read book Combining Pattern Classifiers written by Ludmila I. Kuncheva and published by John Wiley & Sons. This book was released on 2014-08-13 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of Combining Pattern Classifiers was published in 2004. Dr. Kuncheva has plucked from the rich landscape of recent classifier ensemble literature the topics, methods, and algorithms that will guide the reader toward a deeper understanding of the fundamentals, design, and applications of classifier ensemble methods. Thoroughly updated, with MATLAB® code and practice data sets throughout, Combining Pattern Classifiers includes: Coverage of Bayes decision theory and experimental comparison of classifiers Essential ensemble methods such as Bagging, Random forest, AdaBoost, Random subspace, Rotation forest, Random oracle, and Error Correcting Output Code, among others Chapters on classifier selection, diversity, and ensemble feature selection With firm grounding in the fundamentals of pattern recognition, and featuring more than 140 illustrations, Combining Pattern Classifiers, Second Edition is a valuable reference for postgraduate students, researchers, and practitioners in computing and engineering.
