SubDEx: Exploring ratings in subjective databases

Sihem Amer-Yahia, Tova Milo, Brit Youngmann

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

2 Scopus citations

Abstract

We demonstrate SubDEx, a dedicated framework for Subjective Data Exploration (SDE). SubDEx enables the joint exploration of items, people, and people's opinions on items, in a guided multi-step process where each step aggregates the most useful and diverse trends in the form of rating maps. Because of the large search space of possible rating maps, we leverage pruning strategies to enable interactive running times. We demonstrate the need for a dedicated SDE framework and the effectiveness and efficiency of our approach, by interacting with the ICDE'21 participants who will act as data analysts.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE 37th International Conference on Data Engineering, ICDE 2021
PublisherIEEE Computer Society
Pages2653-2656
Number of pages4
ISBN (Electronic)9781728191843
DOIs
StatePublished - Apr 2021
Event37th IEEE International Conference on Data Engineering, ICDE 2021 - Virtual, Chania, Greece
Duration: 19 Apr 202122 Apr 2021

Publication series

NameProceedings - International Conference on Data Engineering
Volume2021-April
ISSN (Print)1084-4627

Conference

Conference37th IEEE International Conference on Data Engineering, ICDE 2021
Country/TerritoryGreece
CityVirtual, Chania
Period19/04/2122/04/21

Funding

FundersFunder number
European Union s Horizon 2020 research and innovation program
Horizon 2020 Framework Programme863410
Israel Science Foundation
Tel Aviv University

    Keywords

    • Data Exploration
    • Recommendation Systems
    • Subjective Data

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