Fuzzy Information Retrieval
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Fuzzy Information Retrieval
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Author : Donald H. Kraft
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2017-01-23
Fuzzy Information Retrieval written by Donald H. Kraft 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 2017-01-23 with Philosophy categories.
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.
Fuzzy Information Retrieval
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Author : Donald H. Kraft
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Fuzzy Information Retrieval written by Donald H. Kraft and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
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.
Fuzzy Sets In Information Retrieval And Cluster Analysis
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Author : S. Miyamoto
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Fuzzy Sets In Information Retrieval And Cluster Analysis written by S. Miyamoto 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 2012-12-06 with Mathematics categories.
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.
Two Approaches For Information Retrieval Through Fuzzy Associations
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Author : Sadaaki Miyamoto
language : en
Publisher:
Release Date : 1988
Two Approaches For Information Retrieval Through Fuzzy Associations written by Sadaaki Miyamoto and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Fuzzy sets categories.
Maximum and minimum operations are used instead of the ordinary sum and product operations on the diagram. Studies on advanced indexing such as clustering of articles are represented as feedbacks on the diagram and properties on fuzzy information retrieval such as level fuzzy sets and set operations on responses of the retrieval system are discussed using the diagram representation."
Fuzzy Logic And The Internet
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Author : Masoud Nikravesh
language : en
Publisher: Springer
Release Date : 2012-11-02
Fuzzy Logic And The Internet written by Masoud Nikravesh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-02 with Technology & Engineering categories.
With the daily addition of million documents and new users, there is no doubt that the World Wide Web (WWW or Web shortly) is still expanding its global information infrastructure. Thanks to low-cost wireless technology, the Web is no more limited to homes or offices, but it is simply everywhere. The Web is so large and growing so rapidly that the 40 million page "WebBase" repository of Inktomi corresponds to only about 4% of the estimated size of the publicly indexable Web as of January 2000 and there is every reason to believe these numbers will all swell significantly in the next few years. This unrestrainable explosion is not bereft of troubles and drawbacks, especially for inexpert users. Probably the most critical problem is the effectiveness of Web search engines: though the Web is rich in providing numerous services, the primary use of the Internet falls in emails and information retrieval activities. Focusing in this latter, any user has felt the frustrating experience to see as result of a search query overwhelming numbers of pages that satisfy the query but that are irrelevant to the user.
Soft Computing In Information Retrieval
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Author : Fabio Crestani
language : en
Publisher: Physica
Release Date : 2013-03-19
Soft Computing In Information Retrieval written by Fabio Crestani and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-19 with Computers categories.
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.
Fuzzy Information Engineering
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Author : Didier Dubois
language : en
Publisher:
Release Date : 1997
Fuzzy Information Engineering written by Didier Dubois and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Computers categories.
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.
Applications Of Fuzzy Sets Theory
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Author : Francesco Masulli
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-06-29
Applications Of Fuzzy Sets Theory written by Francesco Masulli 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 2007-06-29 with Computers categories.
The 7th International Workshop on Fuzzy Logic and Applications, held in Camogli, Italy in July 2007, presented the latest findings in the field. This volume features the refereed proceedings from that meeting. It includes 84 full papers as well as three keynote speeches. The papers are organized into topical sections covering fuzzy set theory, fuzzy information access and retrieval, fuzzy machine learning, and fuzzy architectures and systems.
Soft Computing For Information Processing And Analysis
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Author : Masoud Nikravesh
language : en
Publisher: Springer
Release Date : 2006-07-02
Soft Computing For Information Processing And Analysis written by Masoud Nikravesh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-07-02 with Computers categories.
Search engines, with Google at the top, have become the most heavily used online service, with millions of searches performed every day and many remarkable capabilities. Soft Computing for Information Processing and Analysis includes reports from the front of soft computing in the internet industry and imparts knowledge and understanding of the significance of the field's accomplishments, new developments and future directions. This carefully edited book has evolved from presentations made by the participants of a meeting entitled "Fuzzy Logic and the Internet: Enhancing the Power of the Internet", organized by the Berkeley Initiative in Soft Computing (BISC), University of California, Berkeley. It addresses the important topics of modern search engines such as fuzzy query, decision analysis and support systems, including articles about topics such as Web Intelligence, World Knowledge and Fuzzy Logic (by Lotfi A. Zadeh), perception based information processing, or web intelligence.
Fuzzy Database Modeling Of Imprecise And Uncertain Engineering Information
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Author : Zongmin Ma
language : en
Publisher: Springer
Release Date : 2008-09-12
Fuzzy Database Modeling Of Imprecise And Uncertain Engineering Information written by Zongmin Ma and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-12 with Technology & Engineering categories.
Computer-based information technologies have been extensively used to help industries manage their processes and information systems hereby - come their nervous center. More specially, databases are designed to s- port the data storage, processing, and retrieval activities related to data management in information systems. Database management systems p- vide efficient task support and database systems are the key to impleme- ing industrial data management. Industrial data management requires da- base technique support. Industrial applications, however, are typically data and knowledge intensive applications and have some unique character- tics that makes their management difficult. Besides, some new techniques such as Web, artificial intelligence, and etc. have been introduced into - dustrial applications. These unique characteristics and usage of new te- nologies have put many potential requirements on industrial data mana- ment, which challenge today’s database systems and promote their evolvement. Viewed from database technology, information modeling in databases can be identified at two levels: (conceptual) data modeling and (logical) database modeling. This results in conceptual (semantic) data model and logical database model. Generally a conceptual data model is designed and then the designed conceptual data model will be transformed into a chosen logical database schema. Database systems based on logical database model are used to build information systems for data mana- ment. Much attention has been directed at conceptual data modeling of - dustrial information systems. Product data models, for example, can be views as a class of semantic data models (i. e.