The Turn

Author: Peter Ingwersen
Publisher: Springer Science & Business Media
ISBN: 1402038518
Format: PDF, Mobi
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T The Turn analyzes the research of information seeking and retrieval (IS&R) and proposes a new direction of integrating research in these two areas: the fields should turn off their separate and narrow paths and construct a new avenue of research. An essential direction for this avenue is context as given in the subtitle Integration of Information Seeking and Retrieval in Context. Other essential themes in the book include: IS&R research models, frameworks and theories; search and works tasks and situations in context; interaction between humans and machines; information acquisition, relevance and information use; research design and methodology based on a structured set of explicit variables - all set into the holistic cognitive approach. The present monograph invites the reader into a construction project - there is much research to do for a contextual understanding of IS&R. The Turn represents a wide-ranging perspective of IS&R by providing a novel unique research framework, covering both individual and social aspects of information behavior, including the generation, searching, retrieval and use of information. Regarding traditional laboratory information retrieval research, the monograph proposes the extension of research toward actors, search and work tasks, IR interaction and utility of information. Regarding traditional information seeking research, it proposes the extension toward information access technology and work task contexts. The Turn is the first synthesis of research in the broad area of IS&R ranging from systems oriented laboratory IR research to social science oriented information seeking studies.

Introduction to Information Retrieval

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

Human Interface and the Management of Information Methods Techniques and Tools in Information Design

Author: Michael J. Smith
Publisher: Springer Science & Business Media
ISBN: 3540733450
Format: PDF, Kindle
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This is the first of a two-volume set that constitutes the refereed proceedings of the Symposium on Human Interface 2007, held in Beijing, China in July 2007. It covers design and evaluation methods and techniques, visualizing information, retrieval, searching, browsing and navigation, development methods and techniques, as well as advanced interaction technologies and techniques.

Advances in Information Retrieval

Author: Mounia Lalmas
Publisher: Springer Science & Business Media
ISBN: 3540333479
Format: PDF, ePub, Mobi
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This book constitutes the refereed proceedings of the 28th European Conference on Information Retrieval Research, ECIR 2006, held in London, April 2006. The 37 revised full papers and 28 revised poster papers presented are organized in topical sections on formal models, document and query representation and text understanding, topic identification and news retrieval, clustering and classification, refinement and feedback, performance and peer-to-peer networks, Web search, cross-language retrieval, genomic IR, and much more.

Machine Learning and Statistical Modeling Approaches to Image Retrieval

Author: Yixin Chen
Publisher: Springer Science & Business Media
ISBN: 1402080352
Format: PDF, ePub, Docs
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In the early 1990s, the establishment of the Internet brought forth a revolutionary viewpoint of information storage, distribution, and processing: the World Wide Web is becoming an enormous and expanding distributed digital library. Along with the development of the Web, image indexing and retrieval have grown into research areas sharing a vision of intelligent agents. Far beyond Web searching, image indexing and retrieval can potentially be applied to many other areas, including biomedicine, space science, biometric identification, digital libraries, the military, education, commerce, culture and entertainment. Machine Learning and Statistical Modeling Approaches to Image Retrieval describes several approaches of integrating machine learning and statistical modeling into an image retrieval and indexing system that demonstrates promising results. The topics of this book reflect authors' experiences of machine learning and statistical modeling based image indexing and retrieval. This book contains detailed references for further reading and research in this field as well.

Advances in Information Retrieval

Author: Mohand Boughanem
Publisher: Springer
ISBN: 3642009581
Format: PDF, ePub, Docs
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This book constitutes the refereed proceedings of the 30th annual European Conference on Information Retrieval Research, ECIR 2009, held in Toulouse, France in April 2009. The 42 revised full papers and 18 revised short papers presented together with the abstracts of 3 invited lectures and 25 poster papers were carefully reviewed and selected from 188 submissions. The papers are organized in topical sections on retrieval model, collaborative IR / filtering, learning, multimedia - metadata, expert search - advertising, evaluation, opinion detection, web IR, representation, clustering / categorization as well as distributed IR.

Multidisciplinary Information Retrieval

Author: David Lamas
Publisher: Springer
ISBN: 3319129791
Format: PDF, Docs
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This book constitutes the proceedings of the 7th International Information Retrieval Facility Conference, IRFC 2014, held in Copenhagen, Denmark, November 2014. The 10 papers presented together with one industry paper were carefully reviewed and selected from 13 submissions. The conference aims at bringing young researchers into contact with the industry at an early stage, emphasizing the applicability of IR solutions to real industry cases and the respective challenges.

Charting a New Course Natural Language Processing and Information Retrieval

Author: John I. Tait
Publisher: Springer Science & Business Media
ISBN: 1402034679
Format: PDF, Kindle
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Karen Spärck Jones is one of the major figures of 20th century and early 21st Century computing and information processing. Her ideas have had an important influence on the development of Internet Search Engines. Her contribution has been recognized by awards from the natural language processing, information retrieval and artificial intelligence communities, including being asked to present the prestigious Grace Hopper lecture. She continues to be an active and influential researcher. Her contribution to the scientific evaluation of the effectiveness of such computer systems has been quite outstanding. This book celebrates the life and work of Karen Spärck Jones in her seventieth year. It consists of fifteen new and original chapters written by leading international authorities reviewing the state of the art and her influence in the areas in which Karen Spärck Jones has been active. Although she has a publication record which goes back over forty years, it is clear even the very early work reviewed in the book can be read with profit by those working on recent developments in information processing like bioinformatics and the semantic web.

Visual Information Retrieval Using Java and LIRE

Author: Mathias Lux
Publisher: Morgan & Claypool Publishers
ISBN: 1608459187
Format: PDF
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Visual information retrieval (VIR) is an active and vibrant research area, which attempts at providing means for organizing, indexing, annotating, and retrieving visual information (images and videos) from large, unstructured repositories. The goal of VIR is to retrieve matches ranked by their relevance to a given query, which is often expressed as an example image and/or a series of keywords. During its early years (1995-2000), the research efforts were dominated by content-based approaches contributed primarily by the image and video processing community. During the past decade, it was widely recognized that the challenges imposed by the lack of coincidence between an image's visual contents and its semantic interpretation, also known as semantic gap, required a clever use of textual metadata (in addition to information extracted from the image's pixel contents) to make image and video retrieval solutions efficient and effective. The need to bridge (or at least narrow) the semantic gap has been one of the driving forces behind current VIR research. Additionally, other related research problems and market opportunities have started to emerge, offering a broad range of exciting problems for computer scientists and engineers to work on. In this introductory book, we focus on a subset of VIR problems where the media consists of images, and the indexing and retrieval methods are based on the pixel contents of those images -- an approach known as content-based image retrieval (CBIR). We present an implementation-oriented overview of CBIR concepts, techniques, algorithms, and figures of merit. Most chapters are supported by examples written in Java, using Lucene (an open-source Java-based indexing and search implementation) and LIRE (Lucene Image REtrieval), an open-source Java-based library for CBIR.

Information Retrieval Models

Author: Thomas Roelleke
Publisher: Morgan & Claypool Publishers
ISBN: 1627050795
Format: PDF
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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