SMAP FRAMEWORK: A NOSQL SOLUTION FOR MANAGING A JSON KNOWLEDGE BASE OF SMART POLITICAL DOCUMENTS

Abstract

This paper is devoted to developing a MongoDB framework for managing a JSON Knowledge base of “Smart Political Documents” (SPD). For this purpose, we designed a full knowledge base in a JSON Repository that runs under a MongoDB NoSQL server. The study of the experimentally collected data from the United Nations site has shown that our SPD knowledge base will contain various information using different formats (text, image, audio, video, etc.). The representation of these data requires both hierarchical and relational models. In this respect, we are proposing a NoSQL data model based on both JSON data and relational representation. JSON collections can be related to one another to complete information by special JSON properties. We have also defined a JSON Query Language for SMAP, SPQL (Smart Politics Query Language), which provided a powerful environment for integrating these disparate forms of data. In this paper, we will so describe the repository architecture, a Speech Labeling Technique used to associate information to spoken discourses, and finally, the whole SMArt Political documents (SMAP) framework that is based on a 3-tiers architecture and a Big Data environment with automatic deductions from the analysis of these data. The new system's purpose is to offer the end-user an intelligent way to quickly find the desired documents with all semantic links between them—something impossible in the system's initial state. The actual novelty of the system is represented mainly by the combination of the NoSQL feature with a relational model and an intelligent linked data system.