Knowledge Graphs

  • Querying an Ontology from R

    Querying an Ontology from R

    sreeji

    This article explores how we can query an ontology in GraphDB from R opening it up for analytics. Step-by-step: Query competency questions using R GraphDB exposes a SPARQL endpoint to which you can send SPARQL queries using HTTP POST and parse the JSON results. The endpoint is located at: http://192.168.1.102:7200/repositories/banking…

  • The FtM Data Model (Part 1)

    The FtM Data Model (Part 1)

    sreeji

    The Follow the Money Model consists of four main concepts:entities, references, interstitial entities, and streams 1. Node entities These are the core objects: like Person, Passport, Company as in Figure 1. Each one of them is a standalone entity with its own id, schema and properties (usually, multi-valued lists of…

  • Graph Ontologies

    Graph Ontologies

    sreeji

    Introduction Graph ontologies are the semantic backbone of knowledge graphs. They provide the conceptual structure, allowed relationships, and logical constraints that decide how entities in a knowledge-graph system relate to one another. Graph ontologies offer rich expressiveness, allowing machines to store data and interpret, infer and reason over it. What…

  • Modularity in graphs

    Modularity in graphs

    sreeji

    Modularity is a graph metric that quantifies how strongly a network divides into communities—groups of nodes that are densely connected internally but sparsely connected to the rest of the graph. High modularity means the graph has clear, well‑defined clusters; low modularity means its structure is closer to random (Wikipedia) What…

  • Scaling up the Ontology

    Scaling up the Ontology

    sreeji

    This is a sequel to the previous article on Competency Questions (CQ) where we discussed how CQs can be run in Protégé. If you are not familiar with the concept, it is just a 5 minutes read here Competency Questions… Here, we will discuss scaling the ontology we created into…

  • Comparing Graphs: Why Structure Matters

    sreeji

    Comparing two graphs is not as straightforward as comparing two strings ortwo literals since graphs are composed of nodes and relationships and they canonly be compared against their structure that is their essence. So, when youcompare two graphs, it is not the labels of their nodes that matters, but theshape…

  • Ego‑Networks: Local Structure, Behaviour Patterns, and Graphlets

    sreeji

    This article is based on some of the analysis I have done on the financial transaction datasets as part of financial fraud analysis. I will use the same dataset to explain the concept in concrete terms in the latter part of this article. An egonet (or ego-network) is a very…

  • Understanding Node Similarity and its Uses

    sreeji

    What is Node Similarity? In network analysis, node similarity measures how alike two nodes are with respect to their position and role within a network. Similarity can be based on several criteria, including shared neighbours, network connectivity, or local structural patterns. In graphlet analysis, node similarity is typically assessed by…

  • Competency Questions

    Competency Questions

    sreeji

    At first glance, the term competency question can sound as though it refers to evaluating someone’s competence or expertise. In ontology engineering, however, it means something entirely different but conceptually similar. Competency questions (CQs) are a well-established domain-specific concept used to define the scope and requirements of an ontology. Rather…

  • Creating an Ontology

    Creating an Ontology

    sreeji

    In this article, we will create a mini ontology in the banking domain. We will go through the design following some of the key concepts and also visualising it in some of the tools for the purpose. Mini Banking Ontology (OWL) The banking.owl file we are going to create is…

Latest Notes

View Archive [ -> ]

Browse all notes