A restaurant recommendation system by analyzing ratings and aspects in reviews

  • Yifan Gao
  • , Wenzhe Yu
  • , Pingfu Chao
  • , Rong Zhang*
  • , Aoying Zhou
  • , Xiaoyan Yang
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

Recommender systems are widely deployed to predict the preferences of users to items. They are popular in helping users find movies, books and products in general. In this work, we design a restaurant recommender system based on a novel model that captures correlations between hidden aspects in reviews and numeric ratings. It is motivated by the observation that a user’s preference against an item is affected by different aspects discussed in reviews. Our method first explores topic modeling to discover hidden aspects from review text. Profiles are then created for users and restaurants separately based on aspects discovered in their reviews. Finally, we utilize regression models to detect the user-restaurant relationship. Experiments demonstrate the advantages.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 20th International Conference, DASFAA 2015, Hanoi, Vietnam, April 20-23, 2015 Proceedings, Part II
EditorsMuhammad Aamir Cheema, Matthias Renz, Cyrus Shahabi, Xiaofang Zhou
PublisherSpringer Verlag
Pages526-530
Number of pages5
ISBN (Print)9783319181226
DOIs
StatePublished - 2015
Event20th International Conference on Database Systems for Advanced Applications, DASFAA 2015 - Hanoi, Viet Nam
Duration: 20 Apr 201523 Apr 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9050
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Database Systems for Advanced Applications, DASFAA 2015
Country/TerritoryViet Nam
CityHanoi
Period20/04/1523/04/15

Keywords

  • Hidden aspect
  • Recommender systems
  • Regression model
  • Review analysis

Fingerprint

Dive into the research topics of 'A restaurant recommendation system by analyzing ratings and aspects in reviews'. Together they form a unique fingerprint.

Cite this