I'm running PageRank on a group of nodes of type Paper
, where each node has a property year
. I am currently normalizing each PageRank score by year using the average and standard deviation of PageRank scores for all papers in that year.
I would like to return the top 100 papers (based on scaled PageRank values) for each year. Can I do this in a single query?
The query below calculates the scaled scores and returns the top 100 results overall, rather than the top 100 per year:
CALL algo.pageRank.stream(
'MATCH (p:Paper) WHERE p.year < 2015 RETURN id(p) as id',
'MATCH (p1:Paper)-[:CITES]->(p2:Paper) RETURN id(p1) as source, id(p2) as target',
{graph:'cypher', iterations:20, write:false, concurrency:20})
YIELD node, score
WITH
node.title AS title,
node.year AS year,
score AS page_rank
ORDER BY page_rank DESC
LIMIT 100
WITH year, COLLECT({title: title, page_rank: page_rank}) AS data, AVG(page_rank) AS avg_page_rank, stDev(page_rank) as stdDev
UNWIND data AS d
RETURN year, d.title AS title, ABS(d.page_rank-avg_page_rank)/stdDev AS scaled_score;
Any suggestions would be greatly appreciated!
Try this:
CALL algo.pageRank.stream(
'MATCH (p:Paper) WHERE p.year < 2015 RETURN id(p) as id',
'MATCH (p1:Paper)-[:CITES]->(p2:Paper) RETURN id(p1) as source, id(p2) as target',
{graph:'cypher', iterations:20, write:false, concurrency:20})
YIELD node, score
WITH
node.title AS title,
node.year AS year,
score AS page_rank
ORDER BY page_rank DESC
WITH year, COLLECT({title: title, page_rank: page_rank})[..100] AS data, AVG(page_rank) AS avg_page_rank, stDev(page_rank) as stdDev
UNWIND data AS d
RETURN year, d.title AS title, ABS(d.page_rank-avg_page_rank)/stdDev AS scaled_score;
This query removes the LIMIT
clause and instead keeps the top 100 (sorted) data
items per year.