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dataset-metadata.json

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+{
+  "title": "HESA-v1: Human Emotion + System Adaptation Dataset",
+  "id": "wincode/hesa-v1-human-emotion-system-adaptation",
+  "licenses": [
+    {
+      "name": "MIT"
+    }
+  ],
+  "keywords": [
+    "emotion recognition",
+    "human computer interaction",
+    "affective computing",
+    "synthetic data",
+    "adaptive AI",
+    "stress detection",
+    "cognitive load",
+    "mental health",
+    "productivity",
+    "AGI",
+    "intelligent tutoring",
+    "NLP",
+    "user behavior",
+    "deep learning",
+    "classification"
+  ],
+  "collaborators": [],
+  "data": [
+    {
+      "description": "Full HESA-v1 dataset containing 500 synthetic samples of human emotion states, system telemetry, environmental context, and AI adaptive responses.",
+      "name": "HESA_dataset_v1.json",
+      "totalBytes": 1904937,
+      "columns": [
+        {
+          "name": "sample_id",
+          "description": "Unique sample identifier in format HESA-XXXXX"
+        },
+        {
+          "name": "timestamp",
+          "description": "ISO 8601 datetime of the simulated session"
+        },
+        {
+          "name": "user_profile",
+          "description": "Nested object: age, profession, country, personality_type, experience_level, sleep_hours, stress_level, mental_focus, social_energy"
+        },
+        {
+          "name": "environment",
+          "description": "Nested object: location_type, noise_level, lighting, temperature, time_of_day, weather"
+        },
+        {
+          "name": "system_state",
+          "description": "Nested object: CPU/RAM/battery usage, open apps, typing speed (derived), error frequency (derived), multitasking level"
+        },
+        {
+          "name": "human_behavior",
+          "description": "Nested object: emotion (28 categories), intensity, facial expression, voice tone, frustration signals, cognitive load, learning state"
+        },
+        {
+          "name": "conversation_context",
+          "description": "Nested object: user message, conversation goal, topic, urgency level, communication style"
+        },
+        {
+          "name": "ai_system_response",
+          "description": "Nested object: assistant response, UI adaptation, notification strategy, music recommendation, focus mode, wellness suggestion"
+        },
+        {
+          "name": "long_term_memory",
+          "description": "Nested object: historical behavior pattern, previous emotional state, productivity trend, burnout risk, learning progression"
+        }
+      ]
+    }
+  ]
+}