POI geographic entity recommendation model based on geospatial clustering algorithm

As to the background issues related to POI geographic entity recommendation, we construct a POI geographic entity recommendation model based on geographic spatial clustering algorithm. Firstly, taking ethnic music and cultural scenic spots as the research object, a model is established for the ontology attributes of POI geographical entities. Secondly, based on the geographic spatial attributes of POI geographic entities, a POI geographic entity spatial clustering algorithm is constructed, forming a clustering space with spatial accessibility as the objective function. Finally, based on the ontology attributes and spatial clustering of POI geographic entities, a POI geographic entity recommendation algorithm is established to recommend the optimal POI geographic entities to users based on their interests and transportation costs. We design a validation experiment based on the geographical entities of ethnic music and cultural POIs. The experiment proves that the algorithm we constructed can effectively recommend the optimal POI geographical entities and provide decision support for tourism itinerary planning.