Information Retrieval - Searching in the 21st Century

Foreword. Preface. About the Editors. List of Contributors. Introduction. 1 Information Retrieval Models (Djoerd Hiemstra). 1.1 Introduction. 1.2 Exact Match Models. 1.3 Vector Space Approaches. 1.4 Probabilistic Approaches. 1.5 Summary and Further Reading. Exercises. References. 2 User-centred Evaluation of Information Retrieval Systems (Pia Borlund). 2.1 Introduction. 2.2 The MEDLARS Test. 2.3 The Okapi Project. 2.4 The Interactive IR Evaluation Model. 2.5 Summary. Exercises. References. 3 Multimedia Resource Discovery (Stefan Rüger). 3.1 Introduction. 3.2 Basic Multimedia Search Technologies. 3.3 Challenges of Automated Visual Indexing. 3.4 Added Services. 3.5 Browsing: Lateral and Geotemporal. 3.6 Summary. Exercises. References. 4 Image Users' Needs and Searching Behaviour (Stina Westman). 4.1 Introduction. 4.2 Image Attributes and Users' Needs. 4.3 Image Searching Behaviour. 4.4 New Directions for Image Access. 4.5 Summary. Exercises. References. 5 Web Information Retrieval (Nick Craswell and David Hawking). 5.1 Introduction. 5.2 Distinctive Characteristics of the Web. 5.3 Three Ranking Problems. 5.4 Other Web IR Issues. 5.5 Evaluation of Web Search Effectiveness. 5.6 Summary. Exercises. References. 6 Mobile Search (David Mountain, Hans Myrhaug and Ay_e Göker). 6.1 Introduction: Mobile Search - Why Now? 6.2 Information for Mobile Search. 6.3 Designing for Mobile Search. 6.4 Case Studies. 6.5 Summary. Exercises. References. 7 Context and Information Retrieval (Ay_e Göker, Hans Myrhaug and Ralf Bier). 7.1 Introduction. 7.2 What is Context? 7.3 Context in Information Retrieval. 7.4 Context Modelling and Representation. 7.5 Context and Content. 7.6 Related Topics. 7.7 Evaluating Context-aware IR Systems. 7.8 Summary. Exercises. References. 8 Text Categorisation and Genre in Information Retrieval (Stuart Watt). 8.1 Introduction: What is Text Categorisation? 8.2 How to Build a Text Categorisation System. 8.3 Evaluating Text Categorisation Systems. 8.4 Genre: Text

Ayse Goker

Dr. Ayse Goker is a senior academic at City University London. Her research since the early 90s has focused on developing novel search techniques and environments, with an emphasis on personalised and context-sensitive information retrieval and management systems. These occur particularly within mobile and wireless computing, and also in bibliographic and web environments. Her skills are in identifying user needs and developing innovative systems that meet them. In international collaborations she has also been successful, with extensive experience in designing projects and managing teams to implement them. On the teaching side, Ayse has developed course modules in information systems on several degree programmes at both postgraduate and undergraduate levels.

Ayse is also a company co-founder of AmbieSense Ltd, a mobile information system company. This project began as the AmbieSense EU-IST project at Robert Gordon University, Aberdeen where she was a Reader and project leader. She holds a lifetime Enterprise Fellowship from the Royal Society of Edinburgh and Scottish Enterprise. More recently she was selected for and completed the Massachusetts Institute of Technology (MIT) Entrepreneurship Development Program in Boston, USA.

In her profession, she has been the Chair of the British Computing Society's Specialist Group in Information Retrieval (BCS IRSG) (2000-2005). She was recognised for the totality of her endeavours by becoming a finalist in the Blackberry Women & technology Awards (2005) for Best Woman in Technology (Academia).

John Davies

Dr John Davies leads the Semantic Technology research group at BT. Current interests centre around the application of semantic web technology to business intelligence, information integration, knowledge management and service-oriented environments. He is Project Director of the 12m ACTIVE EU integrated project. He co-founded the European Semantic Web conference series. He is also chairman of the

"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)