Dynamic Information Retrieval Modeling
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Dynamic Information Retrieval Modeling
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Author : Grace Hui Yang
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Dynamic Information Retrieval Modeling written by Grace Hui Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
Big data and human-computer information retrieval (HCIR) are changing IR. They capture the dynamic changes in the data and dynamic interactions of users with IR systems. A dynamic system is one which changes or adapts over time or a sequence of events. Many modern IR systems and data exhibit these characteristics which are largely ignored by conventional techniques. What is missing is an ability for the model to change over time and be responsive to stimulus. Documents, relevance, users and tasks all exhibit dynamic behavior that is captured in data sets typically collected over long time spans and models need to respond to these changes. Additionally, the size of modern datasets enforces limits on the amount of learning a system can achieve. Further to this, advances in IR interface, personalization and ad display demand models that can react to users in real time and in an intelligent, contextual way. In this book we provide a comprehensive and up-to-date introduction to Dynamic Information Retrieval Modeling, the statistical modeling of IR systems that can adapt to change. We define dynamics, what it means within the context of IR and highlight examples of problems where dynamics play an important role. We cover techniques ranging from classic relevance feedback to the latest applications of partially observable Markov decision processes (POMDPs) and a handful of useful algorithms and tools for solving IR problems incorporating dynamics. The theoretical component is based around the Markov Decision Process (MDP), a mathematical framework taken from the field of Artificial Intelligence (AI) that enables us to construct models that change according to sequential inputs. We define the framework and the algorithms commonly used to optimize over it and generalize it to the case where the inputs aren't reliable. We explore the topic of reinforcement learning more broadly and introduce another tool known as a Multi-Armed Bandit which is useful for cases where exploring model parameters is beneficial. Following this we introduce theories and algorithms which can be used to incorporate dynamics into an IR model before presenting an array of state-of-the-art research that already does, such as in the areas of session search and online advertising. Change is at the heart of modern Information Retrieval systems and this book will help equip the reader with the tools and knowledge needed to understand Dynamic Information Retrieval Modeling.
Probabilistic Modeling In Dynamic Information Retrieval
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Author : Marc Sloan
language : en
Publisher:
Release Date : 2016
Probabilistic Modeling In Dynamic Information Retrieval written by Marc Sloan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Information Retrieval Models
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Author : Thomas Roelleke
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2013-07-01
Information Retrieval Models written by Thomas Roelleke and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-01 with Computers categories.
Information Retrieval (IR) models are a core component of IR research and IR systems. The past decade brought a consolidation of the family of IR models, which by 2000 consisted of relatively isolated views on TF-IDF (Term-Frequency times Inverse-Document-Frequency) as the weighting scheme in the vector-space model (VSM), the probabilistic relevance framework (PRF), the binary independence retrieval (BIR) model, BM25 (Best-Match Version 25, the main instantiation of the PRF/BIR), and language modelling (LM). Also, the early 2000s saw the arrival of divergence from randomness (DFR). Regarding intuition and simplicity, though LM is clear from a probabilistic point of view, several people stated: "It is easy to understand TF-IDF and BM25. For LM, however, we understand the math, but we do not fully understand why it works." This book takes a horizontal approach gathering the foundations of TF-IDF, PRF, BIR, Poisson, BM25, LM, probabilistic inference networks (PIN's), and divergence-based models. The aim is to create a consolidated and balanced view on the main models. A particular focus of this book is on the "relationships between models." This includes an overview over the main frameworks (PRF, logical IR, VSM, generalized VSM) and a pairing of TF-IDF with other models. It becomes evident that TF-IDF and LM measure the same, namely the dependence (overlap) between document and query. The Poisson probability helps to establish probabilistic, non-heuristic roots for TF-IDF, and the Poisson parameter, average term frequency, is a binding link between several retrieval models and model parameters. Table of Contents: List of Figures / Preface / Acknowledgments / Introduction / Foundations of IR Models / Relationships Between IR Models / Summary & Research Outlook / Bibliography / Author's Biography / Index
Visualization For Information Retrieval
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Author : Jin Zhang
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-11-24
Visualization For Information Retrieval written by Jin Zhang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-24 with Computers categories.
Information visualization offers a way to reveal hidden patterns in a visual presentation and allows users to seek information from a visual perspective. Readers of this book will gain an in-depth understanding of the current state of information retrieval visualization. They will be introduced to existing problems along with technical and theoretical findings. The book also provides practical details for the implementation of an information retrieval visualization system.
Introduction To Information Retrieval
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Author : Christopher D. Manning
language : en
Publisher: Cambridge University Press
Release Date : 2008-07-07
Introduction To Information Retrieval written by Christopher D. Manning and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-07-07 with Computers categories.
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.
Dynamic Taxonomies And Faceted Search
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Author : Giovanni Maria Sacco
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-08-14
Dynamic Taxonomies And Faceted Search written by Giovanni Maria Sacco and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-14 with Computers categories.
Current access paradigms for the Web, i.e., direct access via search engines or database queries and navigational access via static taxonomies, have recently been criticized because they are too rigid or simplistic to effectively cope with a large number of practical search applications. A third paradigm, dynamic taxonomies and faceted search, focuses on user-centered conceptual exploration, which is far more frequent in search tasks than retrieval using exact specification, and has rapidly become pervasive in modern Web data retrieval, especially in critical applications such as product selection for e-commerce. It is a heavily interdisciplinary area, where data modeling, human factors, logic, inference, and efficient implementations must be dealt with holistically. Sacco, Tzitzikas, and their contributors provide a coherent roadmap to dynamic taxonomies and faceted search. The individual chapters, written by experts in each relevant field and carefully integrated by the editors, detail aspects like modeling, schema design, system implementation, search performance, and user interaction. The basic concepts of each area are introduced, and advanced topics and recent research are highlighted. An additional chapter is completely devoted to current and emerging application areas, including e-commerce, multimedia, multidimensional file systems, and geographical information systems. The presentation targets advanced undergraduates, graduate students and researchers from different areas – from computer science to library and information science – as well as advanced practitioners. Given that research results are currently scattered among very different publications, this volume will allow researchers to get a coherent and comprehensive picture of the state of the art.
Computational Analysis And Understanding Of Natural Languages Principles Methods And Applications
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Author :
language : en
Publisher: Elsevier
Release Date : 2018-08-27
Computational Analysis And Understanding Of Natural Languages Principles Methods And Applications written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-27 with Mathematics categories.
Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications, Volume 38, the latest release in this monograph that provides a cohesive and integrated exposition of these advances and associated applications, includes new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, Inference and Prediction Methods, Random Processes, Bayesian Methods, Machine Learning, Artificial Neural Networks for Natural Language Processing, Information Retrieval, Language Core Tasks, Language Understanding Applications, and more. The synergistic confluence of linguistics, statistics, big data, and high-performance computing is the underlying force for the recent and dramatic advances in analyzing and understanding natural languages, hence making this series all the more important. Provides a thorough treatment of open-source libraries, application frameworks and workflow systems for natural language analysis and understanding Presents new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, and more
Information Retrieval
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Author : Ayse Goker
language : en
Publisher: John Wiley & Sons
Release Date : 2009-12-15
Information Retrieval written by Ayse Goker and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-15 with Technology & Engineering categories.
This book is an essential reference to cutting-edge issues and future directions in information retrieval Information retrieval (IR) can be defined as the process of representing, managing, searching, retrieving, and presenting information. Good IR involves understanding information needs and interests, developing an effective search technique, system, presentation, distribution and delivery. The increased use of the Web and wider availability of information in this environment led to the development of Web search engines. This change has brought fresh challenges to a wider variety of users’ needs, tasks, and types of information. Today, search engines are seen in enterprises, on laptops, in individual websites, in library catalogues, and elsewhere. Information Retrieval: Searching in the 21st Century focuses on core concepts, and current trends in the field. This book focuses on: Information Retrieval Models User-centred Evaluation of Information Retrieval Systems Multimedia Resource Discovery Image Users’ Needs and Searching Behaviour Web Information Retrieval Mobile Search Context and Information Retrieval Text Categorisation and Genre in Information Retrieval Semantic Search The Role of Natural Language Processing in Information Retrieval: Search for Meaning and Structure Cross-language Information Retrieval Performance Issues in Parallel Computing for Information Retrieval This book is an invaluable reference for graduate students on IR courses or courses in related disciplines (e.g. computer science, information science, human-computer interaction, and knowledge management), academic and industrial researchers, and industrial personnel tracking information search technology developments to understand the business implications. Intermediate-advanced level undergraduate students on IR or related courses will also find this text insightful. Chapters are supplemented with exercises to stimulate further thinking.
Advances In Information Retrieval
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Author : Center for Intelligent Information Retrieval
language : en
Publisher: Springer Science & Business Media
Release Date : 2000-04-30
Advances In Information Retrieval written by Center for Intelligent Information Retrieval and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-04-30 with Computers categories.
The NSF Center for Intelligent Information Retrieval (CIIR) was formed in the Computer Science Department of the University of Massachusetts, Amherst, in 1992. Through its efforts in basic research, applied research, and technology transfer, the CIIR has become known internationally as one of the leading research groups in the area of information retrieval. The CIIR focuses on research that results in more effective and efficient access and discovery in large, heterogeneous, distributed text and multimedia databases. The scope of the work that is done in the CIIR is broad and goes significantly beyond `traditional' areas of information retrieval such as retrieval models, cross-lingual search, and automatic query expansion. The research includes both low-level systems issues such as the design of protocols and architectures for distributed search, as well as more human-centered topics such as user interface design, visualization and data mining with text, and multimedia retrieval. Advances in Information Retrieval: Recent Research from the Center for Intelligent Information Retrieval is a collection of papers that covers a wide variety of topics in the general area of information retrieval. Together, they represent a snapshot of the state of the art in information retrieval at the turn of the century and at the end of a decade that has seen the advent of the World-Wide Web. The papers provide overviews and in-depth analysis of theory and experimental results. This book can be used as source material for graduate courses in information retrieval, and as a reference for researchers and practitioners in industry.
Collaborative And Social Information Retrieval And Access Techniques For Improved User Modeling
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Author : Chevalier, Max
language : en
Publisher: IGI Global
Release Date : 2009-04-30
Collaborative And Social Information Retrieval And Access Techniques For Improved User Modeling written by Chevalier, Max and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-30 with Business & Economics categories.
"This book deals with the improvement of user modeling in the context of Collaborative and Social Information Access and Retrieval (CSIRA) techniques"--Provided by publisher.