neo4j错误:类型不匹配:预期的浮点数或整数，但为Node

Question

我在neo4j上有以下数据集

create (recipe1:recipe {name: 'recipe-1'})
create (recipe2:recipe {name: 'recipe-2'})
create (recipe3:recipe {name: 'recipe-3'})
create (recipe4:recipe {name: 'recipe-4'})
create (recipe5:recipe {name: 'recipe-5'})
create (recipe6:recipe {name: 'recipe-6'})
create (user1:user {name: 'user-1'})
create (user2:user {name: 'user-2'})
create (user3:user {name: 'user-3'})
create (user4:user {name: 'user-4'})
create
  (user1)-[:LIKES]->(recipe1),
  (user1)-[:LIKES]->(recipe2),
  (user1)-[:LIKES]->(recipe4),
  (user2)-[:LIKES]->(recipe4),
  (user2)-[:LIKES]->(recipe6),
  (user3)-[:LIKES]->(recipe1),
  (user3)-[:LIKES]->(recipe3),
  (user3)-[:LIKES]->(recipe6),
  (user4)-[:LIKES]->(recipe4)

并试图运行以下查询：

match (user4:user {name: 'user-4'})-[LIKES]->recipe<-[:LIKES]-slm-[:LIKES]->recommendations
where not(user4 = slm) and not(user4-recommendations)
return count(*) AS recommendationsWeight, 
recommendations.name AS name
order by recommendationsWeight DESC, name DESC

但我得到了以下错误：

Type mismatch: expected Float or Integer but was Node (line 2, column 32 (offset: 123))
"where not(user4 = slm) and not(user4-recommendations)"
                                ^

你知道我在这里做错什么了吗？

更新：

在这里，我想对not(user4-recommendations)说的是，user4与之无关的任何建议。例如，考虑以下几点：

match (user4:user {name: 'user-4'}), (recipe1:recipe {name: 'recipe-1'})
create (user4)-[:DISLIKES]->(recipe1)

因此，我的推荐查询结果不应该包括recipe1，因为用户以前与它交互过。

Answer 1

您有一个错误：：-而不是=。不要忘记括号：

match (user4:user {name: 'user-4'})-[LIKES]->
      (recipe)
      <-[:LIKES]-(slm)-[:LIKES]->
      (recommendations)
where not(user4 = slm) and not(user4 = recommendations)
return count(*) AS recommendationsWeight, 
       recommendations.name AS name
order by recommendationsWeight DESC, 
         name DESC

我想你是想建立一个推荐系统。然后，请求将变得更容易(不需要检查，因为它不使用零长路径)：

match (user4:user {name: 'user-4'})
      -[:LIKES]->(recipe)<-[:LIKES]-
      (slm)-[:LIKES]->(recommendations)
where not ( (user4)-[:DISLIKES|LIKES]->(recommendations) )
return recommendations, 
       count(recommendations) as recommendationsWeight  
order by recommendationsWeight desc, 
      recommendations.name asc