K-Graph: Knowledgeable Graph for Text Documents

Abstract Graph databases are applied in many applications, including science and business, due to their low-complexity, low-overheads, lower time-complexity. The graph-based storage offers the advantage of capturing semantic structural information rather than simply using Bag-of-Words technique. An approach called Knowledgeable graphs (K-Graph) is proposed capture knowledge. Documents stored graph nodes. Thanks weighted subgraphs, frequent subgraphs extracted Fast Embedding Referral Table (FERT). table maintained at different levels according headings subheadings documents. It reduces memory overhead, retrieval, access time subgraph needed. authors propose an that will reduce data redundancy a larger extent. With real-world datasets, K-graph’s performance power usage threefold greater current methods. Ninety-nine per cent accuracy demonstrates robustness algorithm.