使用Cypher查询Neo4j电影数据集：高标签量低评分影片合并查询

Got it, let's tackle this. You already have the logic to filter high-tag-count movies (over 3x the average tag count), and now we just need to fold in the low-rating condition. Here's how to combine both requirements efficiently, using Neo4j's movie dataset where :MOVIE nodes have a rating property:

Full Cypher Query #

// Calculate average tag count and average rating first (single pass for efficiency)
MATCH (m:MOVIE)-[r:HAS_TAG]->()
WITH count(r) AS tagnum, m.rating AS rating
WITH avg(tagnum) AS avgtagnum, avg(rating) AS avgrating

// Match movies again, filter for high tag count AND low rating
MATCH (m:MOVIE)-[r:HAS_TAG]->()
WITH m, count(r) AS tagnum, avgtagnum, avgrating
WHERE tagnum > avgtagnum * 3 
  AND m.rating < avgrating  // Use average rating as "low" threshold; replace with fixed value like 5 if preferred
RETURN m.title AS title, tagnum AS tag_count, m.rating AS rating
ORDER BY tagnum DESC, m.rating ASC

Breakdown of the Logic #

• First Block: We first iterate over all tagged movies to compute two key stats in one go: the average number of tags per movie (avgtagnum) and the average rating across all tagged movies (avgrating). This avoids redundant database hits compared to calculating them separately.
• Second Block: We re-match tagged movies, count their tags, and apply your original high-tag filter plus the low-rating check. Using the average rating as the threshold keeps the "low rating" relative to the dataset, but you can swap m.rating < avgrating for a fixed number like m.rating < 5 if you want a hard cutoff.
• Final Return: We output the movie title, tag count, and rating, sorted to show the most tagged (hottest) low-rated movies first.

Quick Adjustment Note #

If some movies in your dataset don't have a rating property, you can add AND exists(m.rating) to the WHERE clause to exclude those, so you only get movies with valid ratings.

内容的提问来源于stack exchange，提问作者guifreballester