Web Recommendations Systems — Scriptorium Liberum

Recommender Systems and the Social Web:

📁 Recommender Systems and the Social Web: Leveraging Tagging Data for Recommender Systems

✍ Fatih Gedikli (auth.) 📂 Library 📅 2013 🏛 Vieweg+Teubner Verlag 🌐 English

There is an increasing demand for recommender systems due to the information overload users are facing on the Web. The goal of a recommender system is to provide personalized recommendations of products or services to users. With the advent of the Social Web, user-generated content has enriched

Recommender Systems for the Social Web

📁 Recommender Systems for the Social Web

✍ José J. Pazos Arias, Ana Fernández Vilas, Rebeca P. Díaz Redondo (auth.) 📂 Library 📅 2012 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

The recommendation of products, content and services cannot be considered newly born, although its widespread application is still in full swing. While its growing success in numerous sectors, the progress of the Social Web has revolutionized the architecture of participation and relationship

Recommender Systems

📁 Recommender Systems

✍ Charu C. Aggarwal 📂 Library 📅 0 🏛 Springer International Publishing, Cham 🌐 English

Recommender Systems

📁 Recommender Systems

✍ Gérald Kembellec; Ghislaine Chartron; Imad Saleh; Gérald Kembellec 📂 Library 📅 2014 🏛 John Wiley & Sons, Incorporated 🌐 English

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

Recommender Systems Handbook

📁 Recommender Systems Handbook

✍ Francesco Ricci, Lior Rokach, Bracha Shapira (auth.), Francesco Ricci, Lior Roka 📂 Library 📅 2011 🏛 Springer US 🌐 English

The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options. Recommender systems have proven

Recommender Systems Handbook

📁 Recommender Systems Handbook

✍ Francesco Ricci, Lior Rokach, Bracha Shapira (auth.), Francesco Ricci, Lior Roka 📂 Library 📅 2011 🏛 Springer US 🌐 English

The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options. Recommender systems have proven