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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
  2. Altmetric Badge
    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
Attention for Chapter 5: Case-Based Recommender Systems: A Unifying View
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Chapter title
Case-Based Recommender Systems: A Unifying View
Chapter number 5
Book title
Intelligent Techniques for Web Personalization
Published by
Springer, Berlin, Heidelberg, January 2005
DOI 10.1007/11577935_5
Book ISBNs
978-3-54-029846-5, 978-3-54-031655-8
Authors

Fabiana Lorenzi, Francesco Ricci, Lorenzi, Fabiana, Ricci, Francesco

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 154 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 4 3%
Netherlands 2 1%
Brazil 2 1%
Spain 2 1%
Ireland 1 <1%
Italy 1 <1%
Chile 1 <1%
Egypt 1 <1%
Hungary 1 <1%
Other 2 1%
Unknown 137 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 41 27%
Student > Master 37 24%
Researcher 17 11%
Student > Doctoral Student 10 6%
Student > Bachelor 9 6%
Other 20 13%
Unknown 20 13%
Readers by discipline Count As %
Computer Science 107 69%
Engineering 8 5%
Business, Management and Accounting 7 5%
Philosophy 1 <1%
Arts and Humanities 1 <1%
Other 4 3%
Unknown 26 17%