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Author: Sarfraz, Muhammad
Publisher: IGI Global
ISBN: 1799810232
Category : Computers
Languages : en
Pages : 374
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Book Description
Information retrieval (IR) is considered to be the science of searching for information from a variety of information sources related to texts, images, sounds, or multimedia. With the rise of the internet and digital databases, updated information retrieval methodologies are essential to ensure the continued facilitation and enhancement of information exchange. Critical Approaches to Information Retrieval Research is a critical scholarly publication that provides multidisciplinary examinations of theoretical innovations and methods in information retrieval technologies including search and storage applications for data, text, image, sound, document, and video retrieval. Featuring a wide range of topics including data mining, machine learning, and ontology, this book is ideal for librarians, software engineers, data scientists, professionals, researchers, information engineers, scientists, practitioners, and academicians working in the fields of computer science, information technology, information and communication sciences, education, health, library, and more.
Author: Sarfraz, Muhammad
Publisher: IGI Global
ISBN: 1799810232
Category : Computers
Languages : en
Pages : 374
Get Book Here
Book Description
Information retrieval (IR) is considered to be the science of searching for information from a variety of information sources related to texts, images, sounds, or multimedia. With the rise of the internet and digital databases, updated information retrieval methodologies are essential to ensure the continued facilitation and enhancement of information exchange. Critical Approaches to Information Retrieval Research is a critical scholarly publication that provides multidisciplinary examinations of theoretical innovations and methods in information retrieval technologies including search and storage applications for data, text, image, sound, document, and video retrieval. Featuring a wide range of topics including data mining, machine learning, and ontology, this book is ideal for librarians, software engineers, data scientists, professionals, researchers, information engineers, scientists, practitioners, and academicians working in the fields of computer science, information technology, information and communication sciences, education, health, library, and more.
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: Djoerd Hiemstra
Publisher: Springer Nature
ISBN: 3030721132
Category : Computers
Languages : en
Pages : 808
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Book Description
This two-volume set LNCS 12656 and 12657 constitutes the refereed proceedings of the 43rd European Conference on IR Research, ECIR 2021, held virtually in March/April 2021, due to the COVID-19 pandemic. The 50 full papers presented together with 11 reproducibility papers, 39 short papers, 15 demonstration papers, 12 CLEF lab descriptions papers, 5 doctoral consortium papers, 5 workshop abstracts, and 8 tutorials abstracts were carefully reviewed and selected from 436 submissions. The accepted contributions cover the state of the art in IR: deep learning-based information retrieval techniques, use of entities and knowledge graphs, recommender systems, retrieval methods, information extraction, question answering, topic and prediction models, multimedia retrieval, and much more.
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: Chengxiang Zhai
Publisher: Springer Nature
ISBN: 3031021304
Category : Computers
Languages : en
Pages : 132
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Book Description
As online information grows dramatically, search engines such as Google are playing a more and more important role in our lives. Critical to all search engines is the problem of designing an effective retrieval model that can rank documents accurately for a given query. This has been a central research problem in information retrieval for several decades. In the past ten years, a new generation of retrieval models, often referred to as statistical language models, has been successfully applied to solve many different information retrieval problems. Compared with the traditional models such as the vector space model, these new models have a more sound statistical foundation and can leverage statistical estimation to optimize retrieval parameters. They can also be more easily adapted to model non-traditional and complex retrieval problems. Empirically, they tend to achieve comparable or better performance than a traditional model with less effort on parameter tuning. This book systematically reviews the large body of literature on applying statistical language models to information retrieval with an emphasis on the underlying principles, empirically effective language models, and language models developed for non-traditional retrieval tasks. All the relevant literature has been synthesized to make it easy for a reader to digest the research progress achieved so far and see the frontier of research in this area. The book also offers practitioners an informative introduction to a set of practically useful language models that can effectively solve a variety of retrieval problems. No prior knowledge about information retrieval is required, but some basic knowledge about probability and statistics would be useful for fully digesting all the details. Table of Contents: Introduction / Overview of Information Retrieval Models / Simple Query Likelihood Retrieval Model / Complex Query Likelihood Model / Probabilistic Distance Retrieval Model / Language Models for Special Retrieval Tasks / Language Models for Latent Topic Analysis / Conclusions
Author: Tie-Yan Liu
Publisher: Springer Science & Business Media
ISBN: 3642142672
Category : Computers
Languages : en
Pages : 282
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Book Description
Due to the fast growth of the Web and the difficulties in finding desired information, efficient and effective information retrieval systems have become more important than ever, and the search engine has become an essential tool for many people. The ranker, a central component in every search engine, is responsible for the matching between processed queries and indexed documents. Because of its central role, great attention has been paid to the research and development of ranking technologies. In addition, ranking is also pivotal for many other information retrieval applications, such as collaborative filtering, definition ranking, question answering, multimedia retrieval, text summarization, and online advertisement. Leveraging machine learning technologies in the ranking process has led to innovative and more effective ranking models, and eventually to a completely new research area called “learning to rank”. Liu first gives a comprehensive review of the major approaches to learning to rank. For each approach he presents the basic framework, with example algorithms, and he discusses its advantages and disadvantages. He continues with some recent advances in learning to rank that cannot be simply categorized into the three major approaches – these include relational ranking, query-dependent ranking, transfer ranking, and semisupervised ranking. His presentation is completed by several examples that apply these technologies to solve real information retrieval problems, and by theoretical discussions on guarantees for ranking performance. This book is written for researchers and graduate students in both information retrieval and machine learning. They will find here the only comprehensive description of the state of the art in a field that has driven the recent advances in search engine development.
Author: Jiaofeng Pan
Publisher: Springer Nature
ISBN: 9811606188
Category : Social Science
Languages : en
Pages : 325
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Book Description
This book provides the readers with the overall latest research on think tanks, summarizing the characteristics of think tanks, revealing the general laws and internal logic of think tank research, applying systems, dialectical views and operations research, system theory, and cybernetics to the problems existing in the research work of think tanks at home and abroad. Based on problem-oriented, evidence-oriented and scientific orientation, this book systematically considers the methodology of think tank research, proposes the DIIS theoretical method system of think tank research, defines the standardization process of think tank research and the quality standard of think tank DIIS, and gives corresponding DIIS to the actual think tank research problem. The method aims to improve the scientificity, effectiveness, and reliability of the research results of think tanks, provide systematic theoretical analysis for think tank research, promote the professional development of think tanks, and better serve the modernization of national governance systems and governance capabilities. This book presents new theoretical and research method support and reference that contribute to macro decision-making departments, management departments, scientific research institutes, universities, and enterprises think tank research related departments, strategic decision makers, think tank managers, think tank researchers, and readers interested in think tanks reading and using. Finally yet importantly, this book embodies the research of think tank as the object of investigation, jumping out of specific social conditions, using systemic thoughts, thinking about the more general role and characteristics of think tanks from the theoretical level, important theoretical issues such as principles and logic systems that think tank research should follow.
Author: Lorna Foyle
Publisher: CRC Press
ISBN: 1315347458
Category : Medical
Languages : en
Pages : 497
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Book Description
Illuminating the Diversity of Cancer and Palliative Care Education examines a myriad of original approaches, techniques, methods, educational strategies and imaginative innovations within this vital field of medicine. Its contributors share a range of educational techniques and tactics from Neuro-Linguistic Programming to creative teaching strategies for bereavement support, allowing readers to reflect on best practice and inventive ways of working which can be used or adapted to suit. This book is an ideal companion to its sister volumes Innovations in Cancer and Palliative Care Education and Delivering Cancer and Palliative Care Education.
Author: Sarfraz, Muhammad
Publisher: IGI Global
ISBN: 1522558330
Category : Computers
Languages : en
Pages : 409
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Book Description
Modern optimization approaches have attracted an increasing number of scientists, decision makers, and researchers. As new issues in this field emerge, different optimization methodologies must be developed and implemented. Exploring Critical Approaches of Evolutionary Computation is a vital scholarly publication that explores the latest developments, methods, approaches, and applications of evolutionary models in a variety of fields. It also emphasizes evolutionary models of computation such as genetic algorithms, evolutionary strategies, classifier systems, evolutionary programming, genetic programming, and related fields such as swarm intelligence and other evolutionary computation techniques. Highlighting a range of pertinent topics such as neural networks, data mining, and data analytics, this book is designed for IT developers, IT theorists, computer engineers, researchers, practitioners, and upper-level students seeking current research on enhanced information exchange methods and practical aspects of computational systems.
Author: Paul Baker
Publisher: Routledge
ISBN: 1317532082
Category : Language Arts & Disciplines
Languages : en
Pages : 228
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Book Description
Contemporary corpus linguists use a wide variety of methods to study discourse patterns. This volume provides a systematic comparison of various methodological approaches in corpus linguistics through a series of parallel empirical studies that use a single corpus dataset to answer the same overarching research question. Ten contributing experts each use a different method to address the same broadly framed research question: In what ways does language use in online Q+A forum responses differ across four world English varieties (India, Philippines, United Kingdom, and United States)? Contributions will be based on analysis of the same 400,000 word corpus from online Q+A forums, and contributors employ methodologies including corpus-based discourse analysis, audience perceptions, Multi-Dimensional analysis, pragmatic analysis, and keyword analysis. In their introductory and concluding chapters, the volume editors compare and contrast the findings from each method and assess the degree to which ‘triangulating’ multiple approaches may provide a more nuanced understanding of a research question, with the aim of identifying a set of complementary approaches which could arguably take into account analytical blind spots. Baker and Egbert also consider the importance of issues such as researcher subjectivity, type of annotation, the limitations and affordances of different corpus tools, the relative strengths of qualitative and quantitative approaches, and the value of considering data or information beyond the corpus. Rather than attempting to find the ‘best’ approach, the focus of the volume is on how different corpus linguistic methodologies may complement one another, and raises suggestions for further methodological studies which use triangulation to enrich corpus-related research.
