MapView: Exploring Datasets via Unsupervised View Recommendation
Buenos Aires de Carvalho, Denis Mayr Lima Martins, Fernando Buarque de Lima Neto · 2021
Exploring large datasets in search for valuable insights requires time and sufficient technical knowledge. In order to alleviate this task, we propose and implemented a prototype of a data exploration tool. It is based on Self-Organizing Maps (SOM) and helps non-technical users with limited technical expertise and time. Our proposed approach employs SOM as a clustering mechanism to group and recommend exploratory data views to the user. This recommendation process can also be personalized to meet user’s intention in an interactive manner. Experimental results show that the reported prototype is effective in recommending valuable views, hence, being of aid in data exploration tasks.