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RECSYS
2015
ACM

Recommender Systems for the People - Enhancing Personalization in Web Augmentation

3 years 4 months ago
Recommender Systems for the People - Enhancing Personalization in Web Augmentation
Web augmentation techniques allow the adaptation of websites on client side using browser extensions or plug-ins designed to run dedicated user scripts. However, while number and variety of such scripts from publicly available repositories have grown remarkably in recent years, they usually neglect the user’s personal profile or individual preferences, and therefore fail to provide enhanced personalized services. At the same time recommender systems have become powerful tools to improve personalization on the Web. Yet, many popular websites lack this functionality, e. g., for missing financial incentive. Therefore, we present a novel approach to empower user script developers to build more personalized augmenters by utilizing collaborative filtering functionality as an external service. Thus, script writers can build recommender systems into arbitrary websites, in fact operating across multiple website domains, while guarding privacy and supplying provenance information. This pap...
Martin Wischenbart, Sergio Firmenich, Gustavo Ross
Added 17 Apr 2016
Updated 17 Apr 2016
Type Journal
Year 2015
Where RECSYS
Authors Martin Wischenbart, Sergio Firmenich, Gustavo Rossi, Manuel Wimmer
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