Abstract
Consumer reviews are dominating consumer purchase decisions, and restaurant (cuisine) reviews are one of the most popular genres of consumer reviews. In contrast to traditional named entity recognition (NER) targets, cuisine names are promising targets that were neglected in previous studies. This study proposes a novel cuisine name extraction algorithm, which can extract cuisine names from restaurant reviews effectively with satisfying performance. Based on the algorithm, we processed more than 12,000 Chinese restaurant reviews and generated a "cuisine map", showing the most popular dishes of restaurants in a map-view to help users make good purchase decisions.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
