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Towards a Rule-Based Visualization Recommendation System

Year 2021

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 scenarios to prove the effectiveness and the feasibility of our approach.

Details

13th International Conference on Knowledge Discovery and Information Retrieval (KDIR 2021)

Authors

Presented at

KDIR 2021, 2021 , PT.

Published in

International Conference on Knowledge Discovery and Information Retrieval(KDIR 2021) .

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