Exploring folksonomy and cooking procedures to boost cooking recipe recommendation

Lijuan Yu, Qing Li, Haoran Xie, Yi Cai

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

13 Citations (Scopus)


Recommender systems have gained great popularity in Internet applications in recent years, due to that they facilitate users greatly in information retrieval despite the explosive data growth. Similar to other popular domains such as the movie-, music-, and book- recommendations, cooking recipe selection is also a daily activity in which user experiences can be greatly improved by adopting appropriate recommendation strategies. Based on content-based and collaborative filtering approaches, we present in this paper a comprehensive recipe recommendation framework encompassing the modeling of the recipe cooking procedures and adoption of folksonomy to boost the recommendations. Empirical studies are conducted on a real data set to show that our method outperforms baselines in the recipe domain.

Original languageEnglish
Title of host publicationWeb Technologies and Applications - 13th Asia-Pacific Web Conference, APWeb 2011, Proceedings
Number of pages12
Publication statusPublished - 28 Apr 2011
Externally publishedYes
Event13th Asia-Pacific Conference on Web Technology, APWeb 2011 - Beijing, China
Duration: 18 Apr 201120 Apr 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6612 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference13th Asia-Pacific Conference on Web Technology, APWeb 2011

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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