Personalized Recommendations for the Web 3D

Authors:
Bartek Ochab;Nicolas Neubauer;Klaus Obermayer
Affiliations:
Neural Information Processing Group, Technische Universität Berlin, Germany;Neural Information Processing Group, Technische Universität Berlin, Germany;Neural Information Processing Group, Technische Universität Berlin, Germany
Venue:
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Year:
2008

Citing 3
Cited 0

Pairwise Data Clustering by Deterministic Annealing

IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernels and Distances for Structured Data

Machine Learning
Unifying user-based and item-based collaborative filtering approaches by similarity fusion

SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval

Quantified Score

Hi-index	0.00

Visualization

Abstract

We introduce the Second Life Location Recommender System (SLLoRS). This system lets users rate and tag locations within the 3D environment Second Life in order to provide personalized recommendations on a collaborative basis. We demonstrate the system as an in-world application and explore some of the general challenges of applying recommendation systems to 3D online environments, like the implementation of data-intensive applications facing restricted computational resources and the segmentation of recommendations in a continuous input space.