Teaching and Learning in Information Retrieval

Author: Efthimis Efthimiadis
Publisher: Springer Science & Business Media
ISBN: 9783642225116
Format: PDF, Kindle
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Information Retrieval has become a very active research field in the 21st century. Many from academia and industry present their innovations in the field in a wide variety of conferences and journals. Companies transfer this new knowledge directly to the general public via services such as web search engines in order to improve their information seeking experience. In parallel, teaching IR is turning into an important aspect of IR generally, not only because it is necessary to impart effective search techniques to make the most of the IR tools available, but also because we must provide a good foundation for those students who will become the driving force of future IR technologies. There are very few resources for teaching and learning in IR, the major problem which this book is designed to solve. The objective is to provide ideas and practical experience of teaching and learning IR, for those whose job requires them to teach in one form or another, and where delivering IR courses is a major part of their working lives. In this context of providing a higher profile for teaching and learning as applied to IR, the co-editor of this book, Efthimis Efthimiathis, had maintained a leading role in teaching and learning within the domain of IR for a number of years. This book represents a posthumous example of his efforts in the area, as he passed away in April 2011. This book, his book, is dedicated to his memory.

Introduction to Information Retrieval

Author: Christopher D. Manning
Publisher: Cambridge University Press
ISBN: 1139472100
Format: PDF, ePub, Mobi
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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.

New Directions in Cognitive Information Retrieval

Author: Amanda Spink
Publisher: Springer Science & Business Media
ISBN: 1402040148
Format: PDF, ePub
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New Directions in Cognitive Information Retrieval presents an exciting new direction for research into cognitive oriented information retrieval (IR) research, a direction based on an analysis of the user’s problem situation and cognitive behavior when using the IR system. This contrasts with the current dominant IR research paradigm which concentrates on improving IR system matching performance. The chapters describe the leading edge concepts and models of cognitive IR that explore the nexus between human cognition, information and the social conditions that drive humans to seek information using IR systems. Chapter topics include: Polyrepresentation, cognitive overlap and the boomerang effect, Multitasking while conducting the search, Knowledge Diagram Visualizations of the topic space to facilitate user assimilation of information, Task, relevance, selection state, knowledge need and knowledge behavior, search training built into the search, children’s collaboration for school projects, and other cognitive perspectives on IR concepts and issues.

Effective Information Retrieval from the Internet

Author: Alison Stacey
Publisher: Elsevier
ISBN: 1780631766
Format: PDF, Mobi
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Effective Information Retrieval from the Internet discusses practical strategies which enable the advanced web user to locate information effectively and to form a precise evaluation of the accuracy of that information. Although the book provides a brief but thorough review of the technologies which are available for these purposes, most of the book concerns practical ‘future-proof’ techniques which are independent of changes in the tools available. For example, the book covers: how to retrieve salient information quickly; how to remove or compensate for bias; and tuition of novice Internet users. Importantly, the book enables readers to develop strategies which will continue to be useful despite the rapidly-evolving state of the Internet and Internet technologies - it is not about technological tricks Enables readers to be aware of and compensate for bias and errors which are ubiquitous on the Internet Provides contemporary information on the deficiencies in web skills of novice users as well as practical techniques for teaching such users

Issues in the Use of Neural Networks in Information Retrieval

Author: Iuliana F. Iatan
Publisher: Springer
ISBN: 3319438719
Format: PDF, Mobi
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This book highlights the ability of neural networks (NNs) to be excellent pattern matchers and their importance in information retrieval (IR), which is based on index term matching. The book defines a new NN-based method for learning image similarity and describes how to use fuzzy Gaussian neural networks to predict personality.It introduces the fuzzy Clifford Gaussian network, and two concurrent neural models: (1) concurrent fuzzy nonlinear perceptron modules, and (2) concurrent fuzzy Gaussian neural network modules.Furthermore, it explains the design of a new model of fuzzy nonlinear perceptron based on alpha level sets and describes a recurrent fuzzy neural network model with a learning algorithm based on the improved particle swarm optimization method.

Works as Entities for Information Retrieval

Author: Richard Smiraglia
Publisher: Routledge
ISBN: 1136410430
Format: PDF, Mobi
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Examine domain-specific research about works and the problems inherent in their storage and retrieval! This book addresses the issue of focusing on known-item identification and retrieval vs. collocation and retrieval of works in the construction of catalogs. Works as Entities for Information Retrieval reports significant research on the role of works as key entities for information retrieval, focusing on the importance of works in information-need and the importance of recognizing and using the work entity in the construction of bibliographic databases, Internet search engines, etc. This single source brings together librarians and scholars from around the world—the United States, Denmark, Canada, Australia, and India—to examine the most recent research on works and on systems to facilitate their retrieval. They share their expertise on essential aspects of works cataloging, including: record clustering for works of fiction ways to define and categorize video works conceptualizing the bibliographic record as text the semiotics of scientific works performed works and AACR2R ways to catalog scientific models cataloging digitized rare books and electronic texts cataloging cartographic materials as works—with three fascinating case studies and more! Works as Entities for Information Retrieval will bring you up to date on essential aspects of works-related cataloging, including analyzing networks of related works; canonicity and the rate of evolution of works; epistemology and taxonomy; user-stipulated interaction with catalog displays of works; searcher-defined attributes of bibliographic works; works in relation to digital resources; and domain-specific analyses of video, scientific, cartographic, performance, theological, and digital works. Make it a part of your professional collection today!

Intelligent Music Information Systems Tools and Methodologies

Author: Shen, Jialie
Publisher: IGI Global
ISBN: 1599046652
Format: PDF, ePub
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Modern technology and the development of user-centric applications have grown to encompass many of our everyday routines and interests. Such advances in music data management and information retrieval techniques have crossed the boundaries of expertise from researchers to developers to professionals in the music industry. Intelligent Music Information Systems: Tools and Methodologies provides comprehensive description and analysis into the use of music information retrieval from the data management perspective, and thus provides libraries in academic, commercial, and other settings with a complete reference for multimedia system applications.

Modern Information Retrieval

Author: Ricardo Baeza-Yates
Publisher: Addison-Wesley Professional
ISBN: 9780321416919
Format: PDF, Mobi
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This is a rigorous and complete textbook for a first course on information retrieval from the computer science perspective. It provides an up-to-date student oriented treatment of information retrieval including extensive coverage of new topics such as web retrieval, web crawling, open source search engines and user interfaces. From parsing to indexing, clustering to classification, retrieval to ranking, and user feedback to retrieval evaluation, all of the most important concepts are carefully introduced and exemplified. The contents and structure of the book have been carefully designed by the two main authors, with individual contributions coming from leading international authorities in the field, including Yoelle Maarek, Senior Director of Yahoo! Research Israel; Dulce Poncele´on IBM Research; and Malcolm Slaney, Yahoo Research USA. This completely reorganized, revised and enlarged second edition of Modern Information Retrieval contains many new chapters and double the number of pages and bibliographic references of the first edition, and a companion website www.mir2ed.org with teaching material. It will prove invaluable to students, professors, researchers, practitioners, and scholars of this fascinating field of information retrieval.

Data Analysis Machine Learning and Applications

Author: Christine Preisach
Publisher: Springer Science & Business Media
ISBN: 9783540782469
Format: PDF, Docs
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Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl). The conference was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007.