A NoSQL Approach for Aspect Mining of Cultural Heritage Streaming Data
Gerasimos Vonitsanos, Andreas Kanavos, Alaa Mohasseb, Dimitrios K. Tsolis · 2019
Aspect mining constitutes an essential part of delivering concise and, perhaps more importantly, accurately tailored cultural content. With the advent of social media, there is a data abundance so that analytics can be reliably designed for ultimately providing valuable information towards a given product or service. Naturally representing and efficiently processing a large number of opinions can be implemented with the use of streaming technologies. Big data analytics are especially important in the case of cultural content management where reviews and opinions may be analyzed in order to extract meaningful representations. In this paper, a NoSQL database method for aspect mining of a cultural heritage scenario by taking advantage of Apache Spark streaming architecture is presented.