Suggestion analysis for food recipe improvement

Abstract

Suggestion analysis for food recipe improvement is to identify helpful suggestions from user comments to improve the recipes. Consequently, user comments about food recipes are classified into two groups that are comments with suggestions or without suggestions. The word information from modified lexicons and created rules for interpreting meaning are applied to analyze those comments or opinions. Natural language processing and text analysis are included in the proposed analysis technique. The automate comment analysis can help both users to choose the preferred food recipes and recipe authors to develop their own creative recipes. To summarize food recipe improvement, the user comments are collected and grouped into suggestion comments and other comments. The evaluation of proposed suggestion analysis shows that the accuracy and precision of comment classification are more than 70%.