Automatic recipe cuisine classification by ingredients

Han Su, Ting Wei Lin, Cheng Te Li, Man Kwan Shan, Janet Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

Abstract

With the growth of recipe sharing services, online cooking recipes associated with ingredients and cooking procedures are available. Many recipe sharing sites have devoted to the development of recipe recommendation mechanism. While most food related research has been on recipe recommendation, little effort has been done on analyzing the correlation between recipe cuisines and ingredients. In this paper, we aim to investigate the underlying cuisineingredient connections by exploiting the classification techniques, including associative classification and support vector machine. Our study conducted on food.com data provides insights about which cuisines are the most similar and what are the essential ingredients for a cuisine, with an application to automatic cuisine labeling for recipes.

Original languageEnglish
Title of host publicationUbiComp 2014 - Adjunct Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PublisherAssociation for Computing Machinery, Inc
Pages565-570
Number of pages6
ISBN (Electronic)9781450330473
DOIs
Publication statusPublished - 2014
Event2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014 - Seattle, United States
Duration: 2014 Sep 132014 Sep 17

Publication series

NameUbiComp 2014 - Adjunct Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Other

Other2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2014
CountryUnited States
CitySeattle
Period14-09-1314-09-17

All Science Journal Classification (ASJC) codes

  • Software

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