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Book Fuzzy Information Retrieval

Download or read book Fuzzy Information Retrieval written by Donald H. Kraft and published by Morgan & Claypool Publishers. This book was released on 2017-01-23 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information retrieval used to mean looking through thousands of strings of texts to find words or symbols that matched a user's query. Today, there are many models that help index and search more effectively so retrieval takes a lot less time. Information retrieval (IR) is often seen as a subfield of computer science and shares some modeling, applications, storage applications and techniques, as do other disciplines like artificial intelligence, database management, and parallel computing. This book introduces the topic of IR and how it differs from other computer science disciplines. A discussion of the history of modern IR is briefly presented, and the notation of IR as used in this book is defined. The complex notation of relevance is discussed. Some applications of IR is noted as well since IR has many practical uses today. Using information retrieval with fuzzy logic to search for software terms can help find software components and ultimately help increase the reuse of software. This is just one practical application of IR that is covered in this book. Some of the classical models of IR is presented as a contrast to extending the Boolean model. This includes a brief mention of the source of weights for the various models. In a typical retrieval environment, answers are either yes or no, i.e., on or off. On the other hand, fuzzy logic can bring in a "degree of" match, vs. a crisp, i.e., strict match. This, too, is looked at and explored in much detail, showing how it can be applied to information retrieval. Fuzzy logic is often times considered a soft computing application and this book explores how IR with fuzzy logic and its membership functions as weights can help indexing, querying, and matching. Since fuzzy set theory and logic is explored in IR systems, the explanation of where the fuzz is ensues. The concept of relevance feedback, including pseudorelevance feedback is explored for the various models of IR. For the extended Boolean model, the use of genetic algorithms for relevance feedback is delved into. The concept of query expansion is explored using rough set theory. Various term relationships is modeled and presented, and the model extended for fuzzy retrieval. An example using the UMLS terms is also presented. The model is also extended for term relationships beyond synonyms. Finally, this book looks at clustering, both crisp and fuzzy, to see how that can improve retrieval performance. An example is presented to illustrate the concepts.

Book Fuzzy Sets in Information Retrieval and Cluster Analysis

Download or read book Fuzzy Sets in Information Retrieval and Cluster Analysis written by S. Miyamoto and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present monograph intends to establish a solid link among three fields: fuzzy set theory, information retrieval, and cluster analysis. Fuzzy set theory supplies new concepts and methods for the other two fields, and provides a common frame work within which they can be reorganized. Four principal groups of readers are assumed: researchers or students who are interested in (a) application of fuzzy sets, (b) theory of information retrieval or bibliographic databases, (c) hierarchical clustering, and (d) application of methods in systems science. Readers in group (a) may notice that the fuzzy set theory used here is very simple, since only finite sets are dealt with. This simplification enables the max min algebra to deal with fuzzy relations and matrices as equivalent entities. Fuzzy graphs are also used for describing theoretical properties of fuzzy relations. This assumption of finite sets is sufficient for applying fuzzy sets to information retrieval and cluster analysis. This means that little theory, beyond the basic theory of fuzzy sets, is required. Although readers in group (b) with little background in the theory of fuzzy sets may have difficulty with a few sections, they will also find enough in this monograph to support an intuitive grasp of this new concept of fuzzy information retrieval. Chapter 4 provides fuzzy retrieval without the use of mathematical symbols. Also, fuzzy graphs will serve as an aid to the intuitive understanding of fuzzy relations.

Book Fuzzy Information Retrieval

Download or read book Fuzzy Information Retrieval written by Donald H. Kraft and published by Springer Nature. This book was released on 2022-06-01 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information retrieval used to mean looking through thousands of strings of texts to find words or symbols that matched a user's query. Today, there are many models that help index and search more effectively so retrieval takes a lot less time. Information retrieval (IR) is often seen as a subfield of computer science and shares some modeling, applications, storage applications and techniques, as do other disciplines like artificial intelligence, database management, and parallel computing. This book introduces the topic of IR and how it differs from other computer science disciplines. A discussion of the history of modern IR is briefly presented, and the notation of IR as used in this book is defined. The complex notation of relevance is discussed. Some applications of IR is noted as well since IR has many practical uses today. Using information retrieval with fuzzy logic to search for software terms can help find software components and ultimately help increase the reuse of software. This is just one practical application of IR that is covered in this book. Some of the classical models of IR is presented as a contrast to extending the Boolean model. This includes a brief mention of the source of weights for the various models. In a typical retrieval environment, answers are either yes or no, i.e., on or off. On the other hand, fuzzy logic can bring in a "degree of" match, vs. a crisp, i.e., strict match. This, too, is looked at and explored in much detail, showing how it can be applied to information retrieval. Fuzzy logic is often times considered a soft computing application and this book explores how IR with fuzzy logic and its membership functions as weights can help indexing, querying, and matching. Since fuzzy set theory and logic is explored in IR systems, the explanation of where the fuzz is ensues. The concept of relevance feedback, including pseudorelevance feedback is explored for the various models of IR. For the extended Boolean model, the use of genetic algorithms for relevance feedback is delved into. The concept of query expansion is explored using rough set theory. Various term relationships is modeled and presented, and the model extended for fuzzy retrieval. An example using the UMLS terms is also presented. The model is also extended for term relationships beyond synonyms. Finally, this book looks at clustering, both crisp and fuzzy, to see how that can improve retrieval performance. An example is presented to illustrate the concepts.

Book Soft Computing in Information Retrieval

Download or read book Soft Computing in Information Retrieval written by Fabio Crestani and published by Physica. This book was released on 2013-03-19 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information retrieval (IR) aims at defining systems able to provide a fast and effective content-based access to a large amount of stored information. The aim of an IR system is to estimate the relevance of documents to users' information needs, expressed by means of a query. This is a very difficult and complex task, since it is pervaded with imprecision and uncertainty. Most of the existing IR systems offer a very simple model of IR, which privileges efficiency at the expense of effectiveness. A promising direction to increase the effectiveness of IR is to model the concept of "partially intrinsic" in the IR process and to make the systems adaptive, i.e. able to "learn" the user's concept of relevance. To this aim, the application of soft computing techniques can be of help to obtain greater flexibility in IR systems.

Book Fuzzy Information Processing

Download or read book Fuzzy Information Processing written by Guilherme A. Barreto and published by Springer. This book was released on 2018-07-03 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the 37th IFSA Conference, NAFIPS 2018, held in Fortaleza, Brazil, in July 2018. The 55 full papers presented were carefully reviewed and selected from 73 submissions. The papers deal with a large spectrum of topics, including theory and applications of fuzzy numbers and sets, fuzzy logic, fuzzy inference systems, fuzzy clustering, fuzzy pattern classification, neuro-fuzzy systems, fuzzy control systems, fuzzy modeling, fuzzy mathematical morphology, fuzzy dynamical systems, time series forecasting, and making decision under uncertainty.

Book Fuzzy Information and Engineering Volume 2

Download or read book Fuzzy Information and Engineering Volume 2 written by Bingyuan Cao and published by Springer Science & Business Media. This book was released on 2009-10-14 with total page 1687 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the proceedings of the Third International Conference on Fuzzy Information and Engineering (ICFIE 2009) held in the famous mountain city Chongqing in Southwestern China, from September 26-29, 2009. Only high-quality papers are included. The ICFIE 2009, built on the success of previous conferences, the ICFIE 2007 (Guangzhou, China), is a major symposium for scientists, engineers and practitioners in the world to present their updated results, ideas, developments and applications in all areas of fuzzy information and engineering. It aims to strengthen relations between industry research laboratories and universities, and to create a primary symposium for world scientists in fuzzy fields as follows: Fuzzy Information; Fuzzy Sets and Systems; Soft Computing; Fuzzy Engineering; Fuzzy Operation Research and Management; Artificial Intelligence; Fuzzy Mathematics and Systems in Applications, etc.

Book Fuzzy Information Engineering

Download or read book Fuzzy Information Engineering written by Didier Dubois and published by . This book was released on 1997 with total page 728 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy logic allows computer programmers to interpret ambiguous commands that ordinary, rigid programs are unable to decipher. For instance, computers can work with words like "tall" and "expensive" rather than 6'5" or $669.95. This book covers the use of fuzzy logic in the information science and information engineering fields.

Book Fuzzy Sets in Approximate Reasoning and Information Systems

Download or read book Fuzzy Sets in Approximate Reasoning and Information Systems written by J.C. Bezdek and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: Approximate reasoning is a key motivation in fuzzy sets and possibility theory. This volume provides a coherent view of this field, and its impact on database research and information retrieval. First, the semantic foundations of approximate reasoning are presented. Special emphasis is given to the representation of fuzzy rules and specialized types of approximate reasoning. Then syntactic aspects of approximate reasoning are surveyed and the algebraic underpinnings of fuzzy consequence relations are presented and explained. The second part of the book is devoted to inductive and neuro-fuzzy methods for learning fuzzy rules. It also contains new material on the application of possibility theory to data fusion. The last part of the book surveys the growing literature on fuzzy information systems. Each chapter contains extensive bibliographical material. Fuzzy Sets in Approximate Reasoning and Information Systems is a major source of information for research scholars and graduate students in computer science and artificial intelligence, interested in human information processing.

Book Fuzzy Logic and its Applications to Engineering  Information Sciences  and Intelligent Systems

Download or read book Fuzzy Logic and its Applications to Engineering Information Sciences and Intelligent Systems written by Zeungnam Bien and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy technology has emerged as one of the most exciting new concepts available. Fuzzy Logic and its Applications... covers a wide range of the theory and applications of fuzzy logic and related systems, including industrial applications of fuzzy technology, implementing human intelligence in machines and systems. There are four main themes: intelligent systems, engineering, mathematical foundations, and information sciences. Both academics and the technical community will learn how and why fuzzy logic is appreciated in the conceptual, design and manufacturing stages of intelligent systems, gaining an improved understanding of the basic science and the foundations of human reasoning.

Book Natural Language Processing and Information Retrieval

Download or read book Natural Language Processing and Information Retrieval written by Muskan Garg and published by CRC Press. This book was released on 2023-11-28 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the basics and recent advancements in natural language processing and information retrieval in a single volume. It will serve as an ideal reference text for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. This text emphasizes the existing problem domains and possible new directions in natural language processing and information retrieval. It discusses the importance of information retrieval with the integration of machine learning, deep learning, and word embedding. This approach supports the quick evaluation of real-time data. It covers important topics including rumor detection techniques, sentiment analysis using graph-based techniques, social media data analysis, and language-independent text mining. Features: • Covers aspects of information retrieval in different areas including healthcare, data analysis, and machine translation • Discusses recent advancements in language- and domain-independent information extraction from textual and/or multimodal data • Explains models including decision making, random walk, knowledge graphs, word embedding, n-grams, and frequent pattern mining • Provides integrated approaches of machine learning, deep learning, and word embedding for natural language processing • Covers latest datasets for natural language processing and information retrieval for social media like Twitter The text is primarily written for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology.

Book Handbook of Fuzzy Computation

Download or read book Handbook of Fuzzy Computation written by E Ruspini and published by CRC Press. This book was released on 2020-03-05 with total page 1229 pages. Available in PDF, EPUB and Kindle. Book excerpt: Initially conceived as a methodology for the representation and manipulation of imprecise and vague information, fuzzy computation has found wide use in problems that fall well beyond its originally intended scope of application. Many scientists and engineers now use the paradigms of fuzzy computation to tackle problems that are either intractable

Book Fifty Years of Fuzzy Logic and its Applications

Download or read book Fifty Years of Fuzzy Logic and its Applications written by Dan E. Tamir and published by Springer. This book was released on 2015-05-23 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive report on the evolution of Fuzzy Logic since its formulation in Lotfi Zadeh’s seminal paper on “fuzzy sets,” published in 1965. In addition, it features a stimulating sampling from the broad field of research and development inspired by Zadeh’s paper. The chapters, written by pioneers and prominent scholars in the field, show how fuzzy sets have been successfully applied to artificial intelligence, control theory, inference, and reasoning. The book also reports on theoretical issues; features recent applications of Fuzzy Logic in the fields of neural networks, clustering, data mining and software testing; and highlights an important paradigm shift caused by Fuzzy Logic in the area of uncertainty management. Conceived by the editors as an academic celebration of the fifty years’ anniversary of the 1965 paper, this work is a must-have for students and researchers willing to get an inspiring picture of the potentialities, limitations, achievements and accomplishments of Fuzzy Logic-based systems.

Book Readings in Fuzzy Sets for Intelligent Systems

Download or read book Readings in Fuzzy Sets for Intelligent Systems written by Didier J. Dubois and published by Morgan Kaufmann. This book was released on 2014-05-12 with total page 929 pages. Available in PDF, EPUB and Kindle. Book excerpt: Readings in Fuzzy Sets for Intelligent Systems is a collection of readings that explore the main facets of fuzzy sets and possibility theory and their use in intelligent systems. Basic notions in fuzzy set theory are discussed, along with fuzzy control and approximate reasoning. Uncertainty and informativeness, information processing, and membership, cognition, neural networks, and learning are also considered. Comprised of eight chapters, this book begins with a historical background on fuzzy sets and possibility theory, citing some forerunners who discussed ideas or formal definitions very close to the basic notions introduced by Lotfi Zadeh (1978). The reader is then introduced to fundamental concepts in fuzzy set theory, including symmetric summation and the setting of fuzzy logic; uncertainty and informativeness; and fuzzy control. Subsequent chapters deal with approximate reasoning; information processing; decision and management sciences; and membership, cognition, neural networks, and learning. Numerical methods for fuzzy clustering are described, and adaptive inference in fuzzy knowledge networks is analyzed. This monograph will be of interest to both students and practitioners in the fields of computer science, information science, applied mathematics, and artificial intelligence.

Book Computational Intelligence for Information Retrieval

Download or read book Computational Intelligence for Information Retrieval written by Dharmender Saini and published by CRC Press. This book was released on 2021-12-14 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough understanding of the integration of computational intelligence with information retrieval including content-based image retrieval using intelligent techniques, hybrid computational intelligence for pattern recognition, intelligent innovative systems, and protecting and analysing big data on cloud platforms. The book aims to investigate how computational intelligence frameworks are going to improve information retrieval systems. The emerging and promising state-of-the-art of human–computer interaction is the motivation behind this book. The book covers a wide range of topics, starting from the tools and languages of artificial intelligence to its philosophical implications, and thus provides a plethora of theoretical as well as experimental research, along with surveys and impact studies. Further, the book aims to showcase the basics of information retrieval and computational intelligence for beginners, as well as their integration, and challenge discussions for existing practitioners, including using hybrid application of augmented reality, computational intelligence techniques for recommendation systems in big data, and a fuzzy-based approach for characterization and identification of sentiments.

Book Introduction to Information Retrieval

Download or read book Introduction to Information Retrieval written by Christopher D. Manning and published by Cambridge University Press. This book was released on 2008-07-07 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Next Generation Search Engines  Advanced Models for Information Retrieval

Download or read book Next Generation Search Engines Advanced Models for Information Retrieval written by Jouis, Christophe and published by IGI Global. This book was released on 2012-03-31 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent technological progress in computer science, Web technologies, and the constantly evolving information available on the Internet has drastically changed the landscape of search and access to information. Current search engines employ advanced techniques involving machine learning, social networks, and semantic analysis. Next Generation Search Engines: Advanced Models for Information Retrieval is intended for scientists and decision-makers who wish to gain working knowledge about search in order to evaluate available solutions and to dialogue with software and data providers. The book aims to provide readers with a better idea of the new trends in applied research.

Book SIGIR    94

    Book Details:
  • Author : W. Bruce Croft
  • Publisher : Springer Science & Business Media
  • Release : 2012-12-06
  • ISBN : 144712099X
  • Pages : 371 pages

Download or read book SIGIR 94 written by W. Bruce Croft and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information retrieval (IR) is becoming an increasingly important area as scientific, business and government organisations take up the notion of "information superhighways" and make available their full text databases for searching. Containing a selection of 35 papers taken from the 17th Annual SIGIR Conference held in Dublin, Ireland in July 1994, the book addresses basic research and provides an evaluation of information retrieval techniques in applications. Topics covered include text categorisation, indexing, user modelling, IR theory and logic, natural language processing, statistical and probabilistic models of information retrieval systems, routing, passage retrieval, and implementation issues.