Update sample_data.py

sample_data.py

@@ -3,119 +3,84 @@ COMPLEX_SAMPLE_JSON = """
   "central_node": "Artificial Intelligence (AI)",
   "nodes": [
     {
-      "id": "ml",
-      "label": "Machine Learning (ML)",
-      "relationship": "Core Domain",
+      "id": "ml_fundamental",
+      "label": "Machine Learning",
+      "relationship": "is essential for",
       "subnodes": [
         {
-          "id": "sl",
-          "label": "Supervised Learning",
-          "relationship": "Learning Paradigm",
+          "id": "dl_branch",
+          "label": "Deep Learning",
+          "relationship": "for example",
           "subnodes": [
             {
-              "id": "sl_prob",
-              "label": "Probabilistic Models",
-              "relationship": "Approach Type",
-              "subnodes": [
-                {
-                  "id": "nbc",
-                  "label": "Naive Bayes Classifier",
-                  "relationship": "Algorithm Example",
-                  "subnodes": [
-                    {"id": "text_class", "label": "Text Classification", "relationship": "Application"},
-                    {"id": "spam_det", "label": "Spam Detection", "relationship": "Application"}
-                  ]
-                },
-                {
-                  "id": "lda",
-                  "label": "Linear Discriminant Analysis",
-                  "relationship": "Algorithm Example",
-                  "subnodes": [
-                    {"id": "dim_red_lda", "label": "Dimensionality Reduction", "relationship": "Use Case"},
-                    {"id": "face_recog", "label": "Face Recognition", "relationship": "Use Case"}
-                  ]
-                }
-              ]
+              "id": "cnn_example",
+              "label": "CNNs",
+              "relationship": "for example"
             },
             {
-              "id": "sl_det",
-              "label": "Deterministic Models",
-              "relationship": "Approach Type",
-              "subnodes": [
-                {
-                  "id": "svm",
-                  "label": "Support Vector Machines (SVM)",
-                  "relationship": "Algorithm Example",
-                  "subnodes": [
-                    {"id": "image_recog", "label": "Image Recognition", "relationship": "Application"},
-                    {"id": "bioinfo", "label": "Bioinformatics", "relationship": "Application"}
-                  ]
-                },
-                {
-                  "id": "dt",
-                  "label": "Decision Trees",
-                  "relationship": "Algorithm Example",
-                  "subnodes": [
-                    {"id": "credit_scoring", "label": "Credit Scoring", "relationship": "Application"},
-                    {"id": "medical_diag", "label": "Medical Diagnosis", "relationship": "Application"}
-                  ]
-                }
-              ]
+              "id": "rnn_example",
+              "label": "RNNs",
+              "relationship": "for example"
             }
           ]
         },
         {
-          "id": "ul",
-          "label": "Unsupervised Learning",
-          "relationship": "Learning Paradigm",
+          "id": "rl_branch",
+          "label": "Reinforcement Learning",
+          "relationship": "for example",
           "subnodes": [
             {
-              "id": "clus",
-              "label": "Clustering",
-              "relationship": "Task Type",
+              "id": "qlearning_example",
+              "label": "Q-Learning",
+              "relationship": "example"
+            },
+            {
+              "id": "pg_example",
+              "label": "Policy Gradients",
+              "relationship": "example"
+            }
+          ]
+        }
+      ]
+    },
+    {
+      "id": "ai_types",
+      "label": "Types",
+      "relationship": "formed by",
+      "subnodes": [
+        {
+          "id": "agi_type",
+          "label": "AGI",
+          "relationship": "this is",
+          "subnodes": [
+            {
+              "id": "strong_ai",
+              "label": "Strong AI",
+              "relationship": "provoked by",
               "subnodes": [
                 {
-                  "id": "kmeans",
-                  "label": "K-Means Clustering",
-                  "relationship": "Algorithm Example",
-                  "subnodes": [
-                    {"id": "customer_seg", "label": "Customer Segmentation", "relationship": "Application"},
-                    {"id": "document_analysis", "label": "Document Analysis", "relationship": "Application"}
-                  ]
-                },
-                {
-                  "id": "dbscan",
-                  "label": "DBSCAN",
-                  "relationship": "Algorithm Example",
-                  "subnodes": [
-                    {"id": "anomaly_det", "label": "Anomaly Detection", "relationship": "Application"},
-                    {"id": "spatial_data", "label": "Spatial Data Analysis", "relationship": "Application"}
-                  ]
+                  "id": "human_intel",
+                  "label": "Human-level Intel.",
+                  "relationship": "of"
                 }
               ]
-            },
+            }
+          ]
+        },
+        {
+          "id": "ani_type",
+          "label": "ANI",
+          "relationship": "this is",
+          "subnodes": [
             {
-              "id": "dim_red_ul",
-              "label": "Dimensionality Reduction",
-              "relationship": "Task Type",
+              "id": "weak_ai",
+              "label": "Weak AI",
+              "relationship": "provoked by",
               "subnodes": [
                 {
-                  "id": "pca",
-                  "label": "Principal Component Analysis (PCA)",
-                  "relationship": "Algorithm Example",
-                  "subnodes": [
-                    {"id": "feature_ext", "label": "Feature Extraction", "relationship": "Use Case"},
-                    {"id": "noise_red", "label": "Noise Reduction", "relationship": "Use Case"}
-                  ]
-                },
-                {
-                  "id": "tsne",
-                  "label": "t-SNE",
-                  "relationship": "Algorithm Example",
-                  "subnodes": [
-                    {"id": "data_viz", "label": "Data Visualization", "relationship": "Application"},
-                    {"id": "genomics", "label": "Genomics", "relationship": "Application"}
-                  ]
+                  "id": "narrow_tasks",
+                  "label": "Narrow Tasks",
+                  "relationship": "of"
                 }
               ]
             }
@@ -124,119 +89,72 @@ COMPLEX_SAMPLE_JSON = """
       ]
     },
     {
-      "id": "dl",
-      "label": "Deep Learning (DL)",
-      "relationship": "Subfield of ML",
+      "id": "ai_capabilities",
+      "label": "Capabilities",
+      "relationship": "change",
       "subnodes": [
         {
-          "id": "cnn",
-          "label": "Convolutional Neural Networks (CNNs)",
-          "relationship": "Architecture Type",
+          "id": "data_proc",
+          "label": "Data Processing",
+          "relationship": "can",
           "subnodes": [
             {
-              "id": "img_class",
-              "label": "Image Classification",
-              "relationship": "Primary Use",
+              "id": "big_data",
+              "label": "Big Data",
+              "relationship": "as",
               "subnodes": [
                 {
-                  "id": "alexnet",
-                  "label": "AlexNet",
-                  "relationship": "Historic Model",
-                  "subnodes": [
-                    {"id": "imagenet", "label": "ImageNet Challenge", "relationship": "Milestone"},
-                    {"id": "gpu_accel", "label": "GPU Acceleration", "relationship": "Enabling Factor"}
-                  ]
+                  "id": "analysis_example",
+                  "label": "Data Analysis",
+                  "relationship": "example"
                 },
                 {
-                  "id": "resnet",
-                  "label": "ResNet",
-                  "relationship": "Advanced Model",
-                  "subnodes": [
-                    {"id": "residual_con", "label": "Residual Connections", "relationship": "Key Feature"},
-                    {"id": "deeper_nets", "label": "Deeper Networks", "relationship": "Benefit"}
-                  ]
-                }
-              ]
-            },
-            {
-              "id": "obj_det_cnn",
-              "label": "Object Detection",
-              "relationship": "Primary Use",
-              "subnodes": [
-                {
-                  "id": "yolo",
-                  "label": "YOLO (You Only Look Once)",
-                  "relationship": "Real-time Algorithm",
-                  "subnodes": [
-                    {"id": "speed", "label": "High Speed", "relationship": "Advantage"},
-                    {"id": "single_pass", "label": "Single Pass Detection", "relationship": "Mechanism"}
-                  ]
-                },
-                {
-                  "id": "faster_rcnn",
-                  "label": "Faster R-CNN",
-                  "relationship": "Region-based Algorithm",
-                  "subnodes": [
-                    {"id": "region_props", "label": "Region Proposals", "relationship": "Mechanism"},
-                    {"id": "accuracy", "label": "High Accuracy", "relationship": "Advantage"}
-                  ]
+                  "id": "prediction_example",
+                  "label": "Prediction",
+                  "relationship": "example"
                 }
               ]
             }
           ]
         },
         {
-          "id": "rnn",
-          "label": "Recurrent Neural Networks (RNNs)",
-          "relationship": "Architecture Type",
+          "id": "decision_making",
+          "label": "Decision Making",
+          "relationship": "can be",
           "subnodes": [
             {
-              "id": "seq_data",
-              "label": "Sequential Data Processing",
-              "relationship": "Primary Use",
+              "id": "automation",
+              "label": "Automation",
+              "relationship": "as",
               "subnodes": [
                 {
-                  "id": "nlp_rnn",
-                  "label": "Natural Language Processing (NLP)",
-                  "relationship": "Application Area",
-                  "subnodes": [
-                    {"id": "text_gen_rnn", "label": "Text Generation", "relationship": "Specific Task"},
-                    {"id": "sentiment_rnn", "label": "Sentiment Analysis", "relationship": "Specific Task"}
-                  ]
+                  "id": "robotics_example",
+                  "label": "Robotics",
+                  "relationship": "example"
                 },
                 {
-                  "id": "speech_rec",
-                  "label": "Speech Recognition",
-                  "relationship": "Application Area",
-                  "subnodes": [
-                    {"id": "voice_assist", "label": "Voice Assistants", "relationship": "Product Example"},
-                    {"id": "transcription", "label": "Audio Transcription", "relationship": "Task"}
-                  ]
+                  "id": "autonomous_example",
+                  "label": "Autonomous Vehicles",
+                  "relationship": "of one"
                 }
               ]
-            },
+            }
+          ]
+        },
+        {
+          "id": "problem_solving",
+          "label": "Problem Solving",
+          "relationship": "can",
+          "subnodes": [
             {
-              "id": "advanced_rnn",
-              "label": "Advanced RNN Variants",
-              "relationship": "Improvements",
+              "id": "optimization",
+              "label": "Optimization",
+              "relationship": "as is",
               "subnodes": [
                 {
-                  "id": "lstm",
-                  "label": "Long Short-Term Memory (LSTM)",
-                  "relationship": "Variant Type",
-                  "subnodes": [
-                    {"id": "vanishing_grad", "label": "Solves Vanishing Gradients", "relationship": "Benefit"},
-                    {"id": "memory_cells", "label": "Internal Memory Cells", "relationship": "Mechanism"}
-                  ]
-                },
-                {
-                  "id": "gru",
-                  "label": "Gated Recurrent Unit (GRU)",
-                  "relationship": "Variant Type",
-                  "subnodes": [
-                    {"id": "simpler_than_lstm", "label": "Simpler Architecture", "relationship": "Characteristic"},
-                    {"id": "comparable_perf", "label": "Comparable Performance", "relationship": "Characteristic"}
-                  ]
+                  "id": "algorithms_example",
+                  "label": "Algorithms",
+                  "relationship": "for example"
                 }
               ]
             }