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Author: Donald Metzler
Publisher: Springer Science & Business Media
ISBN: 3642228984
Category : Computers
Languages : en
Pages : 174
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Book Description
Commercial Web search engines such as Google, Yahoo, and Bing are used every day by millions of people across the globe. With their ever-growing refinement and usage, it has become increasingly difficult for academic researchers to keep up with the collection sizes and other critical research issues related to Web search, which has created a divide between the information retrieval research being done within academia and industry. Such large collections pose a new set of challenges for information retrieval researchers. In this work, Metzler describes highly effective information retrieval models for both smaller, classical data sets, and larger Web collections. In a shift away from heuristic, hand-tuned ranking functions and complex probabilistic models, he presents feature-based retrieval models. The Markov random field model he details goes beyond the traditional yet ill-suited bag of words assumption in two ways. First, the model can easily exploit various types of dependencies that exist between query terms, eliminating the term independence assumption that often accompanies bag of words models. Second, arbitrary textual or non-textual features can be used within the model. As he shows, combining term dependencies and arbitrary features results in a very robust, powerful retrieval model. In addition, he describes several extensions, such as an automatic feature selection algorithm and a query expansion framework. The resulting model and extensions provide a flexible framework for highly effective retrieval across a wide range of tasks and data sets. A Feature-Centric View of Information Retrieval provides graduate students, as well as academic and industrial researchers in the fields of information retrieval and Web search with a modern perspective on information retrieval modeling and Web searches.
Author: Donald Metzler
Publisher: Springer Science & Business Media
ISBN: 3642228984
Category : Computers
Languages : en
Pages : 174
Get Book Here
Book Description
Commercial Web search engines such as Google, Yahoo, and Bing are used every day by millions of people across the globe. With their ever-growing refinement and usage, it has become increasingly difficult for academic researchers to keep up with the collection sizes and other critical research issues related to Web search, which has created a divide between the information retrieval research being done within academia and industry. Such large collections pose a new set of challenges for information retrieval researchers. In this work, Metzler describes highly effective information retrieval models for both smaller, classical data sets, and larger Web collections. In a shift away from heuristic, hand-tuned ranking functions and complex probabilistic models, he presents feature-based retrieval models. The Markov random field model he details goes beyond the traditional yet ill-suited bag of words assumption in two ways. First, the model can easily exploit various types of dependencies that exist between query terms, eliminating the term independence assumption that often accompanies bag of words models. Second, arbitrary textual or non-textual features can be used within the model. As he shows, combining term dependencies and arbitrary features results in a very robust, powerful retrieval model. In addition, he describes several extensions, such as an automatic feature selection algorithm and a query expansion framework. The resulting model and extensions provide a flexible framework for highly effective retrieval across a wide range of tasks and data sets. A Feature-Centric View of Information Retrieval provides graduate students, as well as academic and industrial researchers in the fields of information retrieval and Web search with a modern perspective on information retrieval modeling and Web searches.
Author: Christopher D. Manning
Publisher: Cambridge University Press
ISBN: 1139472100
Category : Computers
Languages : en
Pages :
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Book Description
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.
Author: Gerald J. Kowalski
Publisher: Springer Science & Business Media
ISBN: 0306470314
Category : Computers
Languages : en
Pages : 323
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Book Description
Chapter 1 places into perspective a total Information Storage and Retrieval System. This perspective introduces new challenges to the problems that need to be theoretically addressed and commercially implemented. Ten years ago commercial implementation of the algorithms being developed was not realistic, allowing theoreticians to limit their focus to very specific areas. Bounding a problem is still essential in deriving theoretical results. But the commercialization and insertion of this technology into systems like the Internet that are widely being used changes the way problems are bounded. From a theoretical perspective, efficient scalability of algorithms to systems with gigabytes and terabytes of data, operating with minimal user search statement information, and making maximum use of all functional aspects of an information system need to be considered. The dissemination systems using persistent indexes or mail files to modify ranking algorithms and combining the search of structured information fields and free text into a consolidated weighted output are examples of potential new areas of investigation. The best way for the theoretician or the commercial developer to understand the importance of problems to be solved is to place them in the context of a total vision of a complete system. Understanding the differences between Digital Libraries and Information Retrieval Systems will add an additional dimension to the potential future development of systems. The collaborative aspects of digital libraries can be viewed as a new source of information that dynamically could interact with information retrieval techniques.
Author: A.V. Gundlapalli
Publisher: IOS Press
ISBN: 1614998302
Category : Medical
Languages : en
Pages : 1440
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Book Description
Medical informatics is a field which continues to evolve with developments and improvements in foundational methods, applications, and technology, constantly offering opportunities for supporting the customization of healthcare to individual patients. This book presents the proceedings of the 16th World Congress of Medical and Health Informatics (MedInfo2017), held in Hangzhou, China, in August 2017, which also marked the 50th anniversary of the International Medical Informatics Association (IMIA). The central theme of MedInfo2017 was "Precision Healthcare through Informatics", and the scientific program was divided into five tracks: connected and digital health; human data science; human, organizational, and social aspects; knowledge management and quality; and safety and patient outcomes. The 249 accepted papers and 168 posters included here span the breadth and depth of sub-disciplines in biomedical and health informatics, such as clinical informatics; nursing informatics; consumer health informatics; public health informatics; human factors in healthcare; bioinformatics; translational informatics; quality and safety; research at the intersection of biomedical and health informatics; and precision medicine. The book will be of interest to all those who wish to keep pace with advances in the science, education, and practice of biomedical and health informatics worldwide.
Author: Krisztian Balog
Publisher: Springer
ISBN: 3319939351
Category : Computers
Languages : en
Pages : 358
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Book Description
This open access book covers all facets of entity-oriented search—where “search” can be interpreted in the broadest sense of information access—from a unified point of view, and provides a coherent and comprehensive overview of the state of the art. It represents the first synthesis of research in this broad and rapidly developing area. Selected topics are discussed in-depth, the goal being to establish fundamental techniques and methods as a basis for future research and development. Additional topics are treated at a survey level only, containing numerous pointers to the relevant literature. A roadmap for future research, based on open issues and challenges identified along the way, rounds out the book. The book is divided into three main parts, sandwiched between introductory and concluding chapters. The first two chapters introduce readers to the basic concepts, provide an overview of entity-oriented search tasks, and present the various types and sources of data that will be used throughout the book. Part I deals with the core task of entity ranking: given a textual query, possibly enriched with additional elements or structural hints, return a ranked list of entities. This core task is examined in a number of different variants, using both structured and unstructured data collections, and numerous query formulations. In turn, Part II is devoted to the role of entities in bridging unstructured and structured data. Part III explores how entities can enable search engines to understand the concepts, meaning, and intent behind the query that the user enters into the search box, and how they can provide rich and focused responses (as opposed to merely a list of documents)—a process known as semantic search. The final chapter concludes the book by discussing the limitations of current approaches, and suggesting directions for future research. Researchers and graduate students are the primary target audience of this book. A general background in information retrieval is sufficient to follow the material, including an understanding of basic probability and statistics concepts as well as a basic knowledge of machine learning concepts and supervised learning algorithms.
Author: Fabio Crestani
Publisher: Springer Science & Business Media
ISBN: 9780792383024
Category : Computers
Languages : en
Pages : 362
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Book Description
A collection of papers proposing, developing, and implementing logical IR models. After an introductory chapter on non-classical logic as the appropriate formalism with which to build IR models, papers are divided into groups on three approaches: logical models, uncertainty models, and meta-models. Topics include preferential models of query by navigation, a logic for multimedia information retrieval, logical imaging and probabilistic information retrieval, and an axiomatic aboutness theory for information retrieval. Can be used as a text for a graduate course on information retrieval or database systems, and as a reference for researchers and practitioners in industry. Annotation copyrighted by Book News, Inc., Portland, OR
Author: Diane Kelly
Publisher: Now Publishers Inc
ISBN: 1601982240
Category : Database management
Languages : en
Pages : 246
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Book Description
Provides an overview and instruction on the evaluation of interactive information retrieval systems with users.
Author: Rick Szostak
Publisher: Springer
ISBN: 3319301489
Category : Computers
Languages : en
Pages : 241
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Book Description
This book proposes a novel approach to classification, discusses its myriad advantages, and outlines how such an approach to classification can best be pursued. It encourages a collaborative effort toward the detailed development of such a classification. This book is motivated by the increased importance of interdisciplinary scholarship in the academy, and the widely perceived shortcomings of existing knowledge organization schemes in serving interdisciplinary scholarship. It is designed for scholars of classification research, knowledge organization, the digital environment, and interdisciplinarity itself. The approach recommended blends a general classification with domain-specific classification practices. The book reaches a set of very strong conclusions: -Existing classification systems serve interdisciplinary research and teaching poorly. -A novel approach to classification, grounded in the phenomena studied rather than disciplines, would serve interdisciplinary scholarship much better. It would also have advantages for disciplinary scholarship. The productivity of scholarship would thus be increased. -This novel approach is entirely feasible. Various concerns that might be raised can each be addressed. The broad outlines of what a new classification would look like are developed. -This new approach might serve as a complement to or a substitute for existing classification systems. -Domain analysis can and should be employed in the pursuit of a general classification. This will be particularly important with respect to interdisciplinary domains. -Though the impetus for this novel approach comes from interdisciplinarity, it is also better suited to the needs of the Semantic Web, and a digital environment more generally. Though the primary focus of the book is on classification systems, most chapters also address how the analysis could be extended to thesauri and ontologies. The possibility of a universal thesaurus is explored. The classification proposed has many of the advantages sought in ontologies for the Semantic Web. The book is therefore of interest to scholars working in these areas as well.
Author: Martin White
Publisher: "O'Reilly Media, Inc."
ISBN: 1449330444
Category : Business & Economics
Languages : en
Pages : 190
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Book Description
Is your organization rapidly accumulating more information than you know how to manage? This book helps you create an enterprise search solution based on more than just technology. Author Martin White shows you how to plan and implement a managed search environment that meets the needs of your business and your employees. Learn why it's vital to have a dedicated staff manage your search technology and support your users. In one survey, 93% of executives said their organization is losing revenue because they're not fully able to use the information they collect. With this book, business managers, IT managers, and information professionals can maximize the value of corporate information and data assets. Use 12 critical factors to gauge your organization's search needs Learn how to make a business case for search Research your user requirements and evaluate your current search solution Create a support team with technical skills and organizational knowledge to manage your solution Set quality guidelines for organizational content and metadata Get an overview of open source and commercial search technology Choose an application based on your requirements, not for its features Make mobile and location-independent search part of your solution
Author: Jerome Dinet
Publisher: John Wiley & Sons
ISBN: 1119015154
Category : Technology & Engineering
Languages : en
Pages : 136
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Book Description
Information retrieval is a central and essential activity. It is indeed difficult to find a human activity that does not need to retrieve information in an environment which is often increasingly digital: moving and navigating, learning, having fun, communicating, informing, making a decision, etc. Most human activities are intimately linked to our ability to search quickly and effectively for relevant information, the stakes are sometimes extremely important: passing an exam, voting, finding a job, remaining autonomous, being socially connected, developing a critical spirit, or simply surviving. The author of this book presents a summary of work undertaken over several years relative to the behaviors and cognitive processes involved in information retrieval in digital environments. He presents several examples of theoretical models and studies to better understand the difficulties, behaviors and strategies of individuals searching for information in digital environments.
