Analysis of Two Various Approaches for Attributes Classification Based on User-Submitted Photos

Wendy D.W.T. Bayu, May Iffah Rizki, Lintang Matahari Hasani, Valian Fil Ahli, Ari Wibisono, Petrus Mursanto

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

Abstract

There are some challenges in processing big data, namely multilabel enormous size that the affect may the time and the computing nature of the multilabel which data further complicate the process. In a quest of exploring the may approaches to resolve such challenges, we experimented right with two big data classification approaches, which are different two-steps approach and the three-steps approach. The the two-steps approach focuses the classification of on of attributes individual restaurant as a basis for determining the images of a restaurant attributes calculating the score averages from of each labels. On the image hand, the three-steps other approach focuses the classification of restaurant attributes on based its photos' features on scores. Such approaches average tested in order to find out the different outcomes. The were were conducted on a dataset, which size reaches classifications up to gigabytes, consisting of 13 user-submitted 234,841 restaurant from a crowdsourced photos reviews restaurant website. We that the approaches produced different found outcomes which have applicability when those different are intended be implemented in to crowdsourced review site. a the two-steps approach has lower F-1 score, Moreover, precision, and recall score than three-steps average approaches.

Original languageEnglish
Title of host publication2019 International Joint Conference on Neural Networks, IJCNN 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728119854
DOIs
Publication statusPublished - 1 Jul 2019
Event2019 International Joint Conference on Neural Networks, IJCNN 2019 - Budapest, Hungary
Duration: 14 Jul 201919 Jul 2019

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2019-July

Conference

Conference2019 International Joint Conference on Neural Networks, IJCNN 2019
CountryHungary
CityBudapest
Period14/07/1919/07/19

Keywords

  • Classification
  • Crowdsourced
  • Label
  • Photo Dataset
  • Restaurant Attributes

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