This book constitutes the refereed proceedings of the 8th International Conference on Persuasive Technology, PERSUASIVE 2013, held in Sydney, NSW, Australia, in April 2013. The 16 revised full papers and 12 revised short papers presented were carefully reviewed and selected from 47 submissions. The papers address not only typical persuasive domains like health and environment, but also cover emerging research topics, such as data safety and evaluation of persuasive technologies.

Ubiquitous user modeling differs from generic user modeling by three additional concepts: ongoing modeling, ongoing sharing, and ongoing exploitation. Systems that share their user models will improve the coverage, the level of detail, and the reliability of the integrated user models and thus allow better functions of adaptation. Ubiquitous user modeling implies new challenges of interchangeability, scalability, scrutability, and privacy.

This volume presents results of a series of workshops on the topic of Ubiquitous User Modeling since 2003 and additional workshops at various other conferences e.g. on User Modeling and Adaptive Hypermedia in the last four years.

The 8 revised full papers presented were carefully reviewed and selected from the best lectures given at the workshops and were significantly extended to be included in the book.

Recommender systems are very popular nowadays, as both an academic research field and services provided by numerous companies for e-commerce, multimedia and Web content. Collaborative-based methods have been the focus of recommender systems research for more than two decades.The unique feature of the compendium is the technical details of collaborative recommenders. The book chapters include algorithm implementations, elaborate on practical issues faced when deploying these algorithms in large-scale systems, describe various optimizations and decisions made, and list parameters of the algorithms.This must-have title is a useful reference materials for researchers, IT professionals and those keen to incorporate recommendation technologies into their systems and services.