Distributed cooking recipe recommendation and adaptation

Qing Li, W. Chen, L. Yu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)


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. Experiments are conducted for the evaluation of the proposed model and a prototype system for cooking recipe recommendation is also presented. © 2013 ACADEMY PUBLISHER.
Original languageEnglish
Pages (from-to)528-537
Number of pages10
JournalJournal of Software
Issue number3
Publication statusPublished - 20 Mar 2013
Externally publishedYes


  • Cooking recipe
  • Distributed information retrieval
  • Recipe adaptation
  • Recommender system

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Artificial Intelligence


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