Recommender Systems
1. Edition November 2014
252 Pages, Hardcover
Wiley & Sons Ltd
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.
2 uses to analyze the recommender systems: the case of social media
3 recommendation systems and social networks, what are the implications for digital marketing?
4 recommenders and Diversity: Exploitation of the long tail and diversity of recommendation lists
5 iSoNTRE: Intelligent transformer social networking environment recommendation engines
6 An approach to recommendation level faceted classification for information retrieval
7 Combining configuration and recommendation to allow convenient interactive configuration by product line
8 Space sémiocognitifs: borders recommender systems
9 The French market of literary prescription networks
10 Presentation of the range of services: Goodreads, a recommendation engine dedicated to books
11 Presentation of the range of services: Nomao, recommender systems and information retrieval
Professor of Documentary Engineering Chair of CNAM, Ghislaine Chartron is director of the National Institute of Science and Technical documentation.
Professor at the University Paris 8, Imad Saleh is the Paragraph laboratory director and director of the graduate school Cognition Language Interaction.
