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Advance in information systems set (volume 4): information and recommender systems

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Table of Contents:
CHAPTER 1 A Few Important Details Before We Begin (Pages: 1-6)
1.1. Information systems
1.2. Decision support systems
1.3. Recommender systems
1.4. Comparisons
1.5. Recommendation versus personalization

CHAPTER 2 Recommender Systems (Pages: 7-27)
2.1. Introduction
2.2. Classification of recommender systems
2.3. User profiles
2.4. Data mining
2.5. Content-based approaches
2.6. Collaborative filtering approaches
2.7. Knowledge-based approaches
2.8. Hybrid approaches
2.9. Other approaches

CHAPTER 3 Key Concepts, Useful Measures and Techniques (Pages: 29-42)
3.1. Vector space model
3.2. Similarity measures
3.3. Dimensionality reduction
3.4. Classification/clustering
3.5. Other techniques
3.6. Comparisons

CHAPTER 4 Practical Implementations (Pages: 43-55)
4.1. Commercial applications
4.2. Databases
4.3. Collaborative environments
4.4. Smart cities
4.5. Early warning systems

CHAPTER 5 Evaluating the Quality of Recommender Systems (Pages: 57-64)
5.1. Data sets, sparsity and errors
5.2. Measures

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Availability

Detail Information

Series Title

Information systems, web and pervasive computing series

Call Number

004 NEG a

Publisher

New Jersey : Wiley., 2015

Collation

viii, 78 hal.; ilus.; 24 cm

Language

English

ISBN/ISSN

9781848217546

Classification

004

Content Type

-

Media Type

-

Carrier Type

-

Edition

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Subject(s)

Information Technology
Informasi, Teori

Specific Detail Info

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Statement of Responsibility

Elsa Negre

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