Title of Research Project
Major
Computer Science
Research Abstract
In the near future, online food delivery service companies would occupy a big market share in the food industry. This project aims to provide factual information from customer reviews as part of the numerous innovations in place to drive business and demands. Natural Language Processing is used to provide a comprehensive view of individual restaurants using technologies like NLTK, SpaCy, Gensim and Sklearn. Data of one million Las Vegas restaurant customer reviews is curated from the Yelp Dataset Challenge. Reviews are pre-processed, split into chunks of phrases and mapped to attributes like food, budget, service etc. These attributes are derived using Topic Modeling techniques like NMF and LDA. Data in these attributes are bucketed into sentiments and aggregated. A customer can glance through a grid of attributes against positive and negative sentiment to gauge and make well-informed decisions. The outcome of the project would benefit customers, clients and also provide sustained business to the online service company.
Faculty Mentor/Advisor
Paul Intrevado
Included in
Databases and Information Systems Commons, Other Computer Sciences Commons, Software Engineering Commons
Yelp Improved : Aggregating Restaurant Reviews
In the near future, online food delivery service companies would occupy a big market share in the food industry. This project aims to provide factual information from customer reviews as part of the numerous innovations in place to drive business and demands. Natural Language Processing is used to provide a comprehensive view of individual restaurants using technologies like NLTK, SpaCy, Gensim and Sklearn. Data of one million Las Vegas restaurant customer reviews is curated from the Yelp Dataset Challenge. Reviews are pre-processed, split into chunks of phrases and mapped to attributes like food, budget, service etc. These attributes are derived using Topic Modeling techniques like NMF and LDA. Data in these attributes are bucketed into sentiments and aggregated. A customer can glance through a grid of attributes against positive and negative sentiment to gauge and make well-informed decisions. The outcome of the project would benefit customers, clients and also provide sustained business to the online service company.
