
- English
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- Available on iOS & Android
Recommender Systems
About this book
Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales.
On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior.
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Information
Table of contents
- Cover
- Contents
- Title Page
- Copyright
- Preface
- 1 General Introduction To Recommender Systems
- 2 Understanding Users" Expectations For Recommender Systems: The Case of Social Media
- 3. Recommender Systems And Social Networks: What Are The Implications For Digital Marketing?
- 4 Recommender Systems And Diversity: Taking Advantage of The Long Tail And The Diversity of Recommendation Lists
- 5 Isontre: Intelligent Transformer of Social Networks Into A Recommendation Engine Environment
- 6 A Two-Level Recommendation Approach For Document Search
- 7 Combining Configuration And Recommendation To Enable An Interactive Guidance of Product Line Configuration
- 8 Semio-Cognitive Spaces: The Frontier of Recommender Systems
- 9 The French-Speaking Literary Prescription Market In Networks
- 10 Presentation of Offered Services: Babelio, A Recommendation Engine Dedicated To Books
- 11 Presentation of The Offer of Services: Nomao, Recommender Systems And Information Search
- List of Authors
- Index