Recipe popularity prediction based on the analysis of social reviews

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publication2013 International Joint Conference on Awareness Science and Technology and Ubi-Media Computing: Can We Realize Awareness via Ubi-Media?, iCAST 2013 and UMEDIA 2013
PublisherIEEE Computer Society
Pages568-572
Publication statusPublished - 2013

Conference

Title2013 International Joint Conference on Awareness Science and Technology, iCAST 2013 and 6th International Conference on Ubi-Media Computing, UMEDIA 2013
PlaceJapan
CityAizuwakamatsu
Period2 - 4 November 2013

Abstract

In social based web services systems, some resources gain popularity while others do not. It would be valuable if we can predict the popularity of certain resource. In this work, we study the recipe popularity prediction problem using the Yelp dataset. We investigate various features that can be extracted and help to improve the performance. In particular, we propose to do the sentiment analysis over the reviews and treat the sentimental scores as one of the features. A polynomial regression model is developed to predict the recipe popularity. The experimental results show that our proposed method outperforms the baseline method. © 2013 IEEE.

Research Area(s)

  • Popularity prediction, Regression, Sentiment analysis, Social network

Citation Format(s)

Recipe popularity prediction based on the analysis of social reviews. / Mao, Xudong; Rao, Yanghui; Li, Qing.
2013 International Joint Conference on Awareness Science and Technology and Ubi-Media Computing: Can We Realize Awareness via Ubi-Media?, iCAST 2013 and UMEDIA 2013. IEEE Computer Society, 2013. p. 568-572 6765504.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with host publication)peer-review