loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Arnab Chakrabarti 1 ; Farhad Ahmad 1 and Christoph Quix 2

Affiliations: 1 Information Systems & Databases, RWTH Aachen University, Germany ; 2 Hochschule Niederrhein, University of Applied Sciences & Fraunhofer FIT, Germany

Keyword(s): Data Visualization, Recommendation Systems, Human-in-the-Loop.

Abstract: Data visualization plays an important role in the analysis of data and the identification of insights and characteristics within the dataset. However, visualizing datasets, especially high dimensional ones, is a very difficult and time-consuming process that requires a great deal of manual effort. The automation of data visualization is done in the form of Visualization Recommendation Systems by detecting factors such as data characteristics and user intended tasks in order to recommend useful visualizations. In this paper, we propose a Visualization Recommendation System, built on a knowledge-based rule engine, that takes minimal user input, extracts important data characteristics and supports a large number of visualization techniques depending on both the data characteristics and the intended tasks of the user. Through our proposed model we show the efficacy of such recommendations for users without any domain expertise. Lastly, we evaluate our system with real-world use case scen arios to prove the effectiveness and the feasibility of our approach. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.216.32.116

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Chakrabarti, A.; Ahmad, F. and Quix, C. (2021). Towards a Rule-based Visualization Recommendation System. In Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KDIR; ISBN 978-989-758-533-3; ISSN 2184-3228, SciTePress, pages 57-68. DOI: 10.5220/0010677100003064

@conference{kdir21,
author={Arnab Chakrabarti. and Farhad Ahmad. and Christoph Quix.},
title={Towards a Rule-based Visualization Recommendation System},
booktitle={Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KDIR},
year={2021},
pages={57-68},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010677100003064},
isbn={978-989-758-533-3},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - KDIR
TI - Towards a Rule-based Visualization Recommendation System
SN - 978-989-758-533-3
IS - 2184-3228
AU - Chakrabarti, A.
AU - Ahmad, F.
AU - Quix, C.
PY - 2021
SP - 57
EP - 68
DO - 10.5220/0010677100003064
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic