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Intelligent Techniques for Web Personalization

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Cover of 'Intelligent Techniques for Web Personalization'

Table of Contents

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    Book Overview
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    Chapter 1 Intelligent Techniques for Web Personalization
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    Chapter 2 Modeling Web Navigation: Methods and Challenges
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    Chapter 3 The Traits of the Personable
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    Chapter 4 Addressing Users’ Privacy Concerns for Improving Personalization Quality: Towards an Integration of User Studies and Algorithm Evaluation
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    Chapter 5 Case-Based Recommender Systems: A Unifying View
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    Chapter 6 Improving the Performance of Recommender Systems That Use Critiquing
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    Chapter 7 Hybrid Systems for Personalized Recommendations
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    Chapter 8 Collaborative Filtering Using Associative Neural Memory
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    Chapter 9 Scaling Down Candidate Sets Based on the Temporal Feature of Items for Improved Hybrid Recommendations
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    Chapter 10 Discovering Interesting Navigations on a Web Site Using SAM I
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    Chapter 11 Personalisation of Web Search
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    Chapter 12 The Compass Filter: Search Engine Result Personalization Using Web Communities
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    Chapter 13 Predicting Web Information Content
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    Chapter 14 Mobile Portal Personalization: Tools and Techniques
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    Chapter 15 IKUM: An Integrated Web Personalization Platform Based on Content Structures and User Behavior
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    Chapter 16 A Semantic-Based User Privacy Protection Framework for Web Services
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    Chapter 17 Web Personalisation for Users Protection: A Multi-agent Method
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