Visual Analytics on Semi-structured Data

Semi-structured documents are a common type of data containing free text in natural language (unstructured data) as well as additional information about the document, or meta-data, typically following a schema or controlled vocabulary (structured data). Simultaneous analysis of unstructured and structured data enables the discovery of hidden relationships that cannot be identified from either of these sources when analyzed independently of each other. In this work, we present a visual text analytics tool for semi-structured documents (ViTA-SSD), that aims to support the user in the exploration and finding of insightful patterns in a visual and interactive manner in a semi-structured collection of documents.


A.J. Soto, R. Kiros, V. Keselj, E. Milios. “Exploratory Visual Analysis and Interactive Pattern Extraction from Semi-Structured Data”, ACM Transactions on Interactive and Intelligent Systems. Vol 5, 3, Article 16, 2015 [paper][videos]