Have2eat: a restaurant finder with review summarization for mobile phones

Authors:
Giuseppe Di Fabbrizio;Narendra Gupta;Sveva Besana;Premkumar Mani
Affiliations:
AT&T Labs - Research, Inc.;AT&T Labs - Research, Inc.;AT&T Interactive - Applied Research;AT&T Interactive - Applied Research
Venue:
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Demonstrations
Year:
2010

Citing 7
Cited 1

Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews

ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Thumbs up?: sentiment classification using machine learning techniques

EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Towards answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences

EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Seeing stars: exploiting class relationships for sentiment categorization with respect to rating scales

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Seeing stars when there aren't many stars: graph-based semi-supervised learning for sentiment categorization

TextGraphs-1 Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing
Seeing several stars: a rating inference task for a document containing several evaluation criteria

PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Capturing the stars: predicting ratings for service and product reviews

SS '10 Proceedings of the NAACL HLT 2010 Workshop on Semantic Search

Speech for Content Creation

International Journal of Mobile Human Computer Interaction

Quantified Score

Hi-index	0.00

Visualization

Abstract

Have2eat is a popular mobile application available for iPhone and Android-based devices that helps users to find and assess nearby restaurants. It lists restaurants located around the device and provides a quick highlight about the opinions expressed by online reviewers. Have2eat summarizes textual reviews by extracting relevant sentences and by automatically generating detailed ratings about specific aspects of the restaurant. A compact one-screen digest allows users to quickly access the information they need, expand to full review pages, and report their experience online by entering ratings and comments.