[Python] Optimizing DBpedia Queries for a Knowledge-Based Movie Recommender System

I am working on creating a Knowledge-Based Recommender System for movies using the MovieLens Small dataset and retrieving additional information from DBpedia. I have implemented a solution that extracts the directors for all the movies in the dataset present in DBpedia, but it is quite slow when loading. Could you suggest a way to speed up the search?

def fetch_director_from_dbpedia(title):
movie_title_clean = normalize_title(title)

print(f"Searching for director of: {movie_title_clean}") # Debug: mostra il titolo del film senza la data
sparql = SPARQLWrapper("http://dbpedia.org/sparql")
sparql.setReturnFormat(JSON)

# Query SPARQL per cercare il regista del film con il titolo esatto
query = f"""
SELECT ?director
WHERE {{
?film rdf:type dbo:Film .
?film foaf:name "{movie_title_clean}"@en .
?film dbo:director ?directorResource .
?directorResource foaf:name ?director .

}}
"""

sparql.setQuery(query)
results = sparql.query().convert()

print(f"Query result: {results}") # Debug: mostra il risultato della query

director = None
if results['results']['bindings']:
for result in results['results']['bindings']:
director = result['director']['value']
print(f"Director found: {director}") # Debug: mostra il regista trovato
else:
print(f"No director found for: {movie_title_clean}") # Debug: mostra se non si trova un regista

return director


Thank you

I expect a list of all directors for the movies present in the dataset, retrieved from DBpedia

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