Case Studies in Adaptive Information Access: Navigation, Search, and Recommendation

Case Studies in Adaptive Information Access: Navigation, Search, and Recommendation

Barry Smyth (University College Dublin, Ireland)
DOI: 10.4018/978-1-60566-032-5.ch002
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Abstract

Everyday hundreds of millions of users turn to the World-Wide Web as their primary source of information during their educational, business and personal lives. The Web is an essential source of businesscritical information but has also changed our personal lives, influencing the way that we learn, play, shop and socialise. During the course of a typical day an increasing number of us will interact with a variety of information services on the Web as we hunt for the information that we need. Very often these services will offer a number of alternative modes of information access and associated interfaces— navigation, search, and recommendation being the most common — each designed to help the user to efficiently fulfilling their current information needs. Navigation, search, and recommendation each have their own set of challenges when it comes to facilitating fast and efficient information access. In this chapter we will consider a number of these challenges and describe how they can be addressed by using techniques that allow information services to respond more intelligently to the needs and preferences of individuals and groups of users. Each challenge will be addressed in the form of a case-study focusing on one particular mode of information access (navigation, search, and recommendation) and an application scenario (mobile portals, Web search, and e-commerce), to describe how user profiling, personalization, and adaptive interface design can be combined to produce a more efficient and effective information service.
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Introduction

The Web is an essential source of business-critical information but has also had a significant impact on our personal lives, influencing the way that we learn, play, shop and socialise. During the course of a typical day an increasing number of us will interact with a variety of information services on the Web as we hunt for the information that we need. Very often these services will offer a number of alternative modes of information access and associated interfaces–navigation, search, and recommendation being the most common–each designed to help the user to efficiently fulfill their current information needs.

One familiar mode of information access sees users navigating or browsing through pages of content, following an appropriate sequence of links to locate the particular item of content that they are seeking. Indeed, for a long time navigation was the dominant form of information access, especially during the early years of the Web, when most users began their information quest at the home page of a major portal such as Yahoo or AOL; information access on the Mobile Internet is still largely dominated by navigation-based portal access (Church, Smyth, Cotter, & Bradley, 2007). Today however, with significant advances in search engine technologies, navigation has largely given way, at least on the traditional Web, to query-based search, which is now the primary form of information access for most Web users. In contrast to navigation, search-based information access aims to engage the user in a more targeted information access session, requesting their current information needs, up-front, in the form of a query, and using this to select and rank pages that are known to be relevant to this query.

Navigation and search are examples of reactive modes of information access, in that they both respond to explicit user input (link selection or search queries). The third mode of information access, recommendation, provides an more proactive information access strategy in which content is automatically suggested to a user in the form of a set of recommendations or suggestions. Recommendation interfaces are now a routine part of many information services, especially e-commerce services, where they are used to make product suggestions to users based on either their past purchase histories or on feedback as an effective mode of cross-selling and up-selling.

Navigation, search, and recommendation each have their own set of challenges when it comes to facilitating fast and efficient information access. In this chapter we will consider a number of these challenges and describe how they can be addressed by using techniques that allow information services to respond more intelligently to the needs and preferences of individuals and groups of users. Each challenge will be addressed in the form of a case-study focusing on one particular mode of information access (navigation, search, and recommendation) and an application scenario (mobile portals, Web search, and e-commerce), to describe how user profiling, personalization, and adaptive interface design can be combined to produce a more efficient and effective information service.

The first case-study will focus on navigation in mobile portals and highlight how today’s mobile users are faced with a significant navigation hurdle when it comes to accessing mobile content. We will describe recent research that speaks to the scale of this problem and describe an effective solution in the form of a technique that automatically adapts portal structure in response to user behaviour. Moreover, this particular solution has now been commercialised by ChangingWorlds Ltd. and is used by leading mobile operators to reduce portal navigation times by 50%, resulting in a significant improvement in the overall user experience and an increase in mobile portal usage by up to 30%.

The second case-study will focus on a critical challenge in Web search, namely how to help existing search engines cope more efficiently with the vague queries that are commonplace in Web search. We will describe a community-based search solution that works in concert with an underlying search engine, to adapt a result-list according to the learned preferences of a community of like-minded searchers. We will describe how this solution can identify and promote results that are likely to be more relevant to a given community of searchers. We will also outline the results of a recent trial in a corporate search scenario, which highlight how this form of promotion can lead to more successful search sessions when compared to a leading search engine.

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Editorial Advisory Board
Table of Contents
Foreword
Barry Smyth
Preface
Constantinos Mourlas, Panagiotis Germanakos
Acknowledgment
Constantinos Mourlas, Panagiotis Germanakos
Chapter 1
Nikos Tsianos, Panagiotis Germanakos, Zacharias Lekkas, Constantinos Mourlas
The plethora of information and services as well as the complicated nature of most Web structures intensify the navigational difficulties that arise... Sample PDF
Assessment of Human Factors in Adaptive Hypermedia Environments
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Chapter 2
Barry Smyth
Everyday hundreds of millions of users turn to the World-Wide Web as their primary source of information during their educational, business and... Sample PDF
Case Studies in Adaptive Information Access: Navigation, Search, and Recommendation
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Chapter 3
Sherry Y. Chen
Web-based instruction is prevalent in educational settings. However, many issues still remain to be investigated. In particular, it is still open... Sample PDF
The Effects of Human Factors on the Use of Web-Based Instruction
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Chapter 4
Gulden Uchyigit
Coping with today’s unprecedented information overload problem necessitates the deployment of personalization services. Typical personalization... Sample PDF
The Next Generation of Personalization Techniques
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Chapter 5
Nancy Alonistioti
This chapter introduces context-driven personalisation of service provision based on a middleware architectural approach. It describes the emerging... Sample PDF
Advanced Middleware Architectural Aspects for Personalised Leading-Edge Services
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Chapter 6
Syed Sibte Raza Abidi
This chapter introduces intelligent information personalization as an approach to personalize the webbased information retrieval experiences based... Sample PDF
Intelligent Information Personalization: From Issues to Strategies
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Chapter 7
Babis Magoutas
This chapter introduces a semantically adaptive interface as a means of measuring the quality of egovernment portals, based on user feedback. The... Sample PDF
A Semantically Adaptive Interface for Measuring Portal Quality in E-Government
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Chapter 8
Fabio Grandi, Federica Mandreoli, Riccardo Martoglia, Enrico Ronchetti, Maria Rita Scalas
While the World Wide Web user is suffering form the disease caused by information overload, for which personalization is one of the treatments which... Sample PDF
Ontology-Based Personalization of E-Government Services
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Chapter 9
Maria Golemati, Costas Vassilakis, Akrivi Katifori, George Lepouras, Constantin Halatsis
Novel and intelligent visualization methods are being developed in order to accommodate user searching and browsing tasks, including new and... Sample PDF
Context and Adaptivity-Driven Visualization Method Selection
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Chapter 10
Honghua Dai
Web usage mining has been used effectively as an approach to automatic personalization and as a way to overcome deficiencies of traditional... Sample PDF
Integrating Semantic Knowledge with Web Usage Mining for Personalization
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Chapter 11
Constantinos Mourlas
One way to implement adaptive software is to allocate resources dynamically during run-time rather than statically at design time. Design of... Sample PDF
Adaptive Presentation and Scheduling of Media Streams on Parallel Storage Servers
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Chapter 12
Gheorghita Ghinea
This study investigated two dimensions of cognitive style, including Verbalizer/Imager and Field Dependent/ Field Independent and their influence on... Sample PDF
Impact of Cognitive Style on User Perception of Dynamic Video Content
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Chapter 13
Mathias Bauer, Alexander Kröner, Michael Schneider, Nathalie Basselin
Limitation of the human memory is a well-known issue that anybody has experienced. This chapter discusses typical components and processes involved... Sample PDF
Building Digital Memories for Augmented Cognition and Situated Support
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Chapter 14
Rafael Morales, Nicolas Van Labeke, Paul Brna, María Elena Chan
It is believed that, with the help of suitable technology, learners and systems can cooperate in building a sufficiently accurate learner model they... Sample PDF
Open Learner Modelling as the Keystone of the Next Generation of Adaptive Learning Environments
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Chapter 15
Klaus Jantke, Christoph Igel, Roberta Sturm
Humans need assistance in learning. This is particularly true when learning is supported by modern information and communication technologies. Most... Sample PDF
From E-Learning Tools to Assistants by Learner Modelling and Adaptive Behavior
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Chapter 16
Violeta Damjanovic, Milos Kravcik
The process of training and learning in Web-based and ubiquitous environments brings a new sense of adaptation. With the development of more... Sample PDF
Using Emotional Intelligence in Personalized Adaptation
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Chapter 17
Yang Wang
This chapter presents a first-of-its-kind survey that systematically analyzes existing privacy-enhanced personalization (PEP) solutions and their... Sample PDF
Technical Solutions for Privacy- Enhanced Personalization
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About the Contributors