Web Document Categorization Using Knowledge Graph and Semantic Textual Topic Detection

In several contexts, the amount of available digital documents increases every day. One of these challenging contexts is the Web. The management of this large amount of information needs more efficient and effective methods and techniques for analyzing data and generate information. Specific application as information retrieval systems have more and more high performances in the document seeking process, but often they lack of semantic understanding about documents topics. In this context, another issue arising from a massive amount of data is the problem of information overload, which affects the quality and performances of information retrieval systems. This work aims to show an approach for document classification based on semantic, which allows a topic detection of analyzed documents using an ontology-based model implemented as a semantic knowledge base using a No SQL graph DB. Finally, we present and discuss experimental results in order to show the effectiveness of our approach.