semantica/cookbook/introduction/Graph_Analytics.ipynb

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        "# Graph Analytics\n",
        "\n",
        "## Overview\n",
        "\n",
        "This notebook demonstrates how to analyze knowledge graphs using Semantica's analytics modules. You'll learn to use `GraphAnalyzer`, `CentralityCalculator`, `CommunityDetector`, and `ConnectivityAnalyzer` to understand graph structure and properties.\n",
        "\n",
        "### Learning Objectives\n",
        "\n",
        "- Use `GraphAnalyzer` for comprehensive graph analysis\n",
        "- Use `CentralityCalculator` to compute centrality measures\n",
        "- Use `CommunityDetector` to find communities in graphs\n",
        "- Use `ConnectivityAnalyzer` to analyze graph connectivity\n",
        "\n",
        "---\n",
        "\n",
        "## Step 1: Graph Analysis\n",
        "\n",
        "Analyze graph structure and properties.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "from semantica.kg import GraphBuilder, GraphAnalyzer\n",
        "from semantica.semantic_extract import NERExtractor, RelationExtractor\n",
        "\n",
        "builder = GraphBuilder()\n",
        "analyzer = GraphAnalyzer()\n",
        "\n",
        "entities = [\n",
        "    {\"id\": \"e1\", \"type\": \"Organization\", \"name\": \"Apple Inc.\", \"properties\": {}},\n",
        "    {\"id\": \"e2\", \"type\": \"Person\", \"name\": \"Tim Cook\", \"properties\": {}},\n",
        "    {\"id\": \"e3\", \"type\": \"Location\", \"name\": \"Cupertino\", \"properties\": {}}\n",
        "]\n",
        "\n",
        "relationships = [\n",
        "    {\"source\": \"e2\", \"target\": \"e1\", \"type\": \"CEO_of\", \"properties\": {}},\n",
        "    {\"source\": \"e1\", \"target\": \"e3\", \"type\": \"located_in\", \"properties\": {}}\n",
        "]\n",
        "\n",
        "kg = builder.build(entities, relationships)\n",
        "\n",
        "metrics = analyzer.compute_metrics(kg)\n",
        "\n",
        "print(f\"Graph metrics:\")\n",
        "print(f\"  Entities: {metrics.get('entity_count', 0)}\")\n",
        "print(f\"  Relationships: {metrics.get('relationship_count', 0)}\")\n",
        "print(f\"  Density: {metrics.get('density', 0):.3f}\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Step 2: Centrality Measures\n",
        "\n",
        "Calculate centrality measures for entities.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "from semantica.kg import CentralityCalculator\n",
        "\n",
        "centrality_calculator = CentralityCalculator()\n",
        "\n",
        "centrality_scores = centrality_calculator.calculate_centrality(kg, measure=\"degree\")\n",
        "\n",
        "print(f\"Centrality scores:\")\n",
        "for entity_id, score in list(centrality_scores.items())[:5]:\n",
        "    print(f\"  {entity_id}: {score:.3f}\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Step 3: Community Detection\n",
        "\n",
        "Detect communities in the graph.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "from semantica.kg import CommunityDetector\n",
        "\n",
        "community_detector = CommunityDetector()\n",
        "\n",
        "communities = community_detector.detect_communities(kg)\n",
        "\n",
        "print(f\"Detected {len(communities)} communities\")\n",
        "for i, community in enumerate(communities[:3], 1):\n",
        "    print(f\"  Community {i}: {len(community)} entities\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Step 4: Connectivity Analysis\n",
        "\n",
        "Analyze graph connectivity.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "from semantica.kg import ConnectivityAnalyzer\n",
        "\n",
        "connectivity_analyzer = ConnectivityAnalyzer()\n",
        "\n",
        "connectivity = connectivity_analyzer.analyze_connectivity(kg)\n",
        "\n",
        "print(f\"Connectivity analysis:\")\n",
        "print(f\"  Is connected: {connectivity.get('is_connected', False)}\")\n",
        "print(f\"  Components: {len(connectivity.get('components', []))}\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Summary\n",
        "\n",
        "You've learned how to analyze knowledge graphs:\n",
        "\n",
        "- **GraphAnalyzer**: Comprehensive graph analysis and metrics\n",
        "- **CentralityCalculator**: Calculate centrality measures\n",
        "- **CommunityDetector**: Detect communities in graphs\n",
        "- **ConnectivityAnalyzer**: Analyze graph connectivity\n",
        "\n",
        "Next: Learn how to assess graph quality in the Graph_Quality notebook.\n"
      ]
    }
  ],
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    "language_info": {
      "name": "python"
    }
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