Cooking Recipe Rating Based on Sentiment

Cooking Recipe Rating Based on Sentiment

Cooking Recipe Rating Based on Sentiment  report in PHP analysis of food recipe comments is to identify user comments about the food recipes to the positive or the negative comments. The proposed method is suitable for analyzing comments or opinions about food recipes by counting the polarity words on the food domain. The benefit of this research is to help users to choose the preferred recipes from different food recipes on online food communities. To analyse food recipes, the comments of each recipe from members of the community will be collected and classified to neutral, positive or negative comments. All recipes’ comment messages are processed using text analytics and the generated polarity lexicon. Therefore, the user can gain the information to make a smart decision. The evaluation of the comment analysis shows that the accuracy of neutral and positive comment classification is about 90%. In addition, the accuracy of negative comment identification is more than 70%. This is one of the best PHP project on Cooking Recipe Rating Based on Sentiment. You can download best PHP project on and report on Cooking Recipe Rating Based on Sentiment. Click here to get complete php projects lists.

Conclusion

Cooking Recipe Rating Based on Sentiment report in PHP At the present time, a huge capacity of information is available over social communities. Opinions or Comments may be contained in various contents, including the information or knowledge. Moreover, opinions or comments from other peoples are very useful in our own decision making. Therefore, the automated technique which can analyse opinions or comments will be the valuable tool to assist users, customers, consumers and providers. For the previous reasons, this research proposed sentiment analysis of food recipe comments on the food domain using the syntactic and semantic information of words and text analysis.

The subjectivity words about the food are also collected and the polarity lexicon is generated. The outcome of the proposed analysis is the software that can analyse sentiments from many contents on comment messages about food recipes. In addition, this proposed method can help the members in the food community to make decisions about preferred food recipes from various recipes. Furthermore, the recipe authors can gain information that how many peoples like or dislike the recipes. In the future work, the personal profiles of people who comment the recipes, e.g. nationality and age, will be collected to analyse recipe comments by the groups of people. You can download PHP project on Cooking Recipe Rating Based on Sentiment easily.

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