Functional Architecture of integrated framework for Facet-based Data Collection and Analysis

Abstract

We present in this paper an integrated framework for collection and analysis of Facet-based text data. The integrated framework consists of four components: (1) user interface, (2) web crawler, (3) data analyzer, and (4) database (DB). User interface is used to set input Facet and option values for web crawling and text data analysis using a graphical user interface (GUI). In fact, it offers outcomes of research by data visualization. The web crawler collects text data from articles posted on the web based on input Facets. The data analyzer classifies papers in "relevant articles" (i.e., word sets to be included on such posts) and "nonrelevant articles" with predefined information. It then analyzes the text data of the relevant articles and visualizes the results of the data analysis. Ultimately, the DB holds the generated text information, the predefined user-defined expertise and the outcomes of data analysis and data visualization. We verify the feasibility of an integrated framework by means of proof of concept (PoC) prototyping. The experimental results show that the implemented prototype reliably collects and analyzes the text data of the articles.