Social navigation of food recipes
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Distributed content-based visual information retrieval system on peer-to-peer networks
ACM Transactions on Information Systems (TOIS)
Trust-Based Community Formation in Peer-to-Peer File Sharing Networks
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
The Knowledge Engineering Review
Client-side web mining for community formation in peer-to-peer environments
ACM SIGKDD Explorations Newsletter
Substructure similarity measurement in chinese recipes
Proceedings of the 17th international conference on World Wide Web
Exploiting peer relations for distributed multimedia information retrieval
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Scalable Retrieval and Mining With Optimal Peer-to-Peer Configuration
IEEE Transactions on Multimedia
| Hi-index | 0.00 |
In this paper, we propose a distributed recipe recommendation mechanism that utilizes social information for adaptive recipe recommendation in a peer-to-peer (P2P) network. A recipe flavor model is first proposed for modeling recipes and validating recipe adaptations. Peers in the network group themselves into communities in which members share common preferences of recipe data. This is helpful to visit more relevant peers when the query scope is fixed thus improve the performance of recommendation. Based on a graph-based recipe representation, we propose a recipe similarity measure and a filtering algorithm to generate candidates of cooking recipes to be recommended. A recipe adaptation method is also proposed in order to better match users' preferences. Simulation experiments are conducted for the evaluation of the proposed model and the results show good performance of it.