Information Retrieval: Searching in the 21st Century / Edition 1

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"This book is an essential reference to cutting-edge issues and future directions in information retrieval Information retrieval (IR) can be defined as the process of representing, managing, searching, retrieving, and presenting information. Good IR involves understanding information needs and interests, developing an effective search technique, system, presentation, distribution and delivery. The increased use of the Web and wider availability of information in this environment led to the development of Web search engines. This change has brought fresh challenges to a wider variety of users' needs, tasks, and types of information. Today, search engines are seen in enterprises, on laptops, in individual websites, in library catalogues, and elsewhere. Information Retrieval: Searching in the 21st Century focuses on core concepts, and current trends in the field. This book focuses on: Information Retrieval Models User-centred Evaluation of Information Retrieval Systems Multimedia Resource Discovery Image Users' Needs and Searching Behaviour Web Information Retrieval Mobile Search Context and Information Retrieval Text Categorisation and Genre in Information Retrieval Semantic Search The Role of Natural Language Processing in Information Retrieval: Search for Meaning and Structure Cross-language Information Retrieval Performance Issues in Parallel Computing for Information Retrieval. This book is an invaluable reference for graduate students on IR courses or courses in related disciplines (e.g. computer science, information science, human-computer interaction, and knowledge management), academic and industrial researchers, and industrial personnel tracking informationsearch technology developments to understand the business implications. Intermediate-advanced level undergraduate students on IR or related courses will also find this text insightful. Chapters are supplemented with exercises to stimulate further thinking"--Provided by publisher.

"The aim of this book is to provide a basis for understanding recent developments in the field and to outline directions for information search technologies. The text presents significant contributions to the research community and industry, covering topics such as the semantic search, natural language processing, parallel information retrieval, image and multimedia retrieval, text categorisation, context technology, cross-language retrieval, and mobile information services. The book is a balanced mixture of theory, practice, tools and applications"--Provided by publisher.

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Editorial Reviews

From the Publisher

“I would recommend Information Retrieval to readers who already have a base of knowledge on core IR concepts." (Inf Retrieval, 9 December 2010)

"The authors have definitely met the challenge of providing a comprehensive volume of factual knowledge on IR fundamentals. I highly recommend the book to those in both academia and industry." (Computing Reviews, 9 May 2011)

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Product Details

  • ISBN-13: 9780470027622
  • Publisher: Wiley
  • Publication date: 12/30/2009
  • Edition number: 1
  • Pages: 295
  • Product dimensions: 6.80 (w) x 9.80 (h) x 0.90 (d)

Table of Contents

1 Information Retrieval Models Djoerd Hiemstra Hiemstra, Djoerd 1

2 User-centred Evaluation of Information Retrieval Systems Pia Borlund Borlund, Pia 21

3 Multimedia Resource Discovery Stefan Ruger Ruger, Stefan 39

4 Image Users' Needs and Searching Behaviour Stina Westman Westman, Stina 63

5 Web Information Retrieval Nick Craswell Craswell, Nick David Hawking Hawking, David 85

6 Mobile Search David Mountain Mountain, David Hans Myrhaug Myrhaug, Hans Ayse Goker Goker, Ayse 103

7 Context and Information Retrieval Ayse Goker Goker, Ayse Hans Myrhaug Myrhaug, Hans Ralf Bierig Bierig, Ralf 131

8 Text Categorisation and Genre in Information Retrieval Stuart Watt Watt, Stuart 159

9 Semantic Search John Davies Davies, John Alistair Duke Duke, Alistair Atanas Kiryakov Kiryakov, Atanas 179

10 The Role of Natural Language Processing in Information Retrieval: Searching for Meaning and Structure Tony Russell-Rose Russell-Rose, Tony Mark Stevenson Stevenson, Mark 215

11 Cross-Language Information Retrieval Daqing He He, Daqing Jianqiang Wang Wang, Jianqiang 233

12 Performance Issues in Parallel Computing for Information Retrieval Andrew MacFarlane MacFarlane, Andrew 255

Solutions to Exercises 273

Index 285

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Customer Reviews

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Sort by: Showing 1 Customer Reviews
  • Posted June 10, 2010

    more from this reviewer

    unresolved problems

    This text is a good explication of the current state of information retrieval. Unsurprisingly the discussion is dominated by the seminal case of the Web. As several chapters relate, prior to the Web this field was dominated by the case where a user [=searcher] would typically hand a query to a specialist [usually a librarian], and the latter would craft an actual query that was input to an IR database. Also, the database was built and maintained by experts. Much of the book describes how the Web differs; a harder case to treat, not least because of the sheer size of the Web corpus.

    One tough problem is tackled in a chapter on multimedia resource discovery. How to search across a corpus of images or video for desired data? This is more difficult than a search of text or HTML files. In turn, this problem leads to largely unresolved subproblems, like the semantic gap. The latter refers to the distance in meaning between scanning an image to extract low level data about its pixels' colours and distribution, and the higher level understanding of what the image is about, in human cognitive terms.

    Barring breakthroughs in artificial intelligence, these problems may be unresolvable. The text shows that current solutions are approximations. One of which is the manual tagging of images and video, so that the tags can be searched as text. Another is at the GUI level, where the searcher can input an image and searching is then done for similar images. A feedback loop is made by the searcher being able to pick an image out of the result set of images, for another iteration of search.

    Unfortunately, this chapter has some example images that are too small for the reader to easily discern. A simple improvement would have been to expand the images, at the cost of a few extra pages.

    Other chapters discuss different challenges. Like picking spam out of a set of email. Existing antispam methods are only briefly discussed, but you get the gist of several ideas.

    Cross language IR is the final chapter. Machine translation is shown to be still quite rough, but it is the only realistic way of analysing huge data sets on the Web. Manual translations are more accurate but simply too slow and costly. We see that MT is greatly improved if there are existing Rosetta stones - pages in 2 languages that have been written to mean the same thing. From this, MT can bootstrap to greatly improve the automated translation of other documents between those languages.

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