Recommendation system based on item and user similarity on restaurants directory online

Aji Achmad Mustofa, Indra Budi

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

5 Citations (Scopus)

Abstract

The growing number of internet companies are demanding the company to innovate through technology. This is also applied to restaurant directory companies, they should give recommendation of restaurant which suit best on customer needs. This study aims to develop a system to provide recommendation for customer in restaurant selection. We merge the item similarity and user similarity features to generate recommendations. Evaluation shows that the recommendation system based on item similarity yields higher F1-measure value when comparing to user similarity.

Original languageEnglish
Title of host publication2018 6th International Conference on Information and Communication Technology, ICoICT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages70-74
Number of pages5
ISBN (Electronic)9781538645710
DOIs
Publication statusPublished - 8 Nov 2018
Event6th International Conference on Information and Communication Technology, ICoICT 2018 - Bandung, Indonesia
Duration: 3 May 20184 May 2018

Publication series

Name2018 6th International Conference on Information and Communication Technology, ICoICT 2018

Conference

Conference6th International Conference on Information and Communication Technology, ICoICT 2018
Country/TerritoryIndonesia
CityBandung
Period3/05/184/05/18

Keywords

  • Item similarity
  • Recommendation system
  • Restaurant recommendation system
  • User similarity

Fingerprint

Dive into the research topics of 'Recommendation system based on item and user similarity on restaurants directory online'. Together they form a unique fingerprint.

Cite this