Create recommendation_system.py

QuantumNexusProtocol/src/ai/recommendation_system.py

@@ -0,0 +1,19 @@
+import pandas as pd
+from sklearn.neighbors import NearestNeighbors
+
+class RecommendationSystem:
+    def __init__(self, data):
+        self.data = data
+
+    def recommend(self, user_id, n_recommendations=5):
+        model = NearestNeighbors(metric='cosine')
+        model.fit(self.data)
+        distances, indices = model.kneighbors(self.data.loc[user_id].values.reshape(1, -1), n_neighbors=n_recommendations + 1)
+        return self.data.index[indices.flatten()[1:]].tolist()
+
+# Example usage
+if __name__ == "__main__":
+    data = pd.DataFrame(np.random.rand(10, 5))  # Simulated user-item interaction data
+    recommender = RecommendationSystem(data)
+    recommendations = recommender.recommend(user_id=0)
+    print(f"Recommendations for User 0: {recommendations}")