I adapted the "9.5.3.3. Pearson Similarity algorithm function sample" query from https://neo4j.com/docs/graph-algorithms/3.5/labs-algorithms/pearson to the yelp sandbox between two users 'Jenn' and 'Audrey'. My query is at the bottom. I was expecting a single similarity score as the output but instead got a list of scores as below. Why am I getting this result? algo.similarity.asVector should have chained all the reviews into two vectors but I'm not sure this is happening in my case.
match (a1:User {name:'Jenn'})-[:WROTE]->(r1)-[:REVIEWS]->(b)
with a1, algo.similarity.asVector(b, r1.stars) as p1Vector
match (a2:User {name:'Audrey'})-[:WROTE]->(r2)-[:REVIEWS]->(b)
with a1, a2, p1Vector, algo.similarity.asVector(b, r2.stars) as p2Vector
return a1.name as from, a2.name as to, algo.similarity.pearson(p1Vector, p2Vector, {vectorType:"maps"}) as similarity