KitWorks Team Study

1. Kit Works Team Study
GraphDB
황원준
2022/04/08

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활용방안
지식그래프, 소셜그래프
시맨틱 웹

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활용방안
자격증명 그래프
개인화,패턴탐지

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활용방안
사기탐지, 추천엔진

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싸이퍼 예시
데이터 확장

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싸이퍼 예시
데이터 제공
MATCH (q:Query)-->(t:Topic)-->(e:Entity)
OPTIONAL MATCH (e)-->(ta:Tag)
WITH q, t, e, collect(ta.name) AS et
ORDER BY q.qc DESC
LIMIT 10
MATCH (t)-->(a:Attribute)
OPTIONAL MATCH (a)-->(ta:Tag)
RETURN q.query AS Query, t.topic AS Topic, e.entity AS Entity, et AS En
tity_Tag, a.attribute AS Attribute, collect(ta.name) as Attribute_Tag

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싸이퍼 예시
데이터 제공
MATCH (q:Query)-->(t:Topic)-->(e:Entity)
OPTIONAL MATCH (e)-->(ta:Tag)
WITH q, t, e, collect(ta.name) AS et
ORDER BY q.qc DESC
LIMIT 10
MATCH (t)-->(a:Attribute)
OPTIONAL MATCH (a)-->(ta:Tag)
RETURN q, t, e, et, a, ta

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싸이퍼 예시
데이터 재구성
MATCH (t:Tag {name:'브랜드'})<--(e:Entity)
RETURN e.entity AS Entity
ORDER BY e.qc DESC
LIMIT 10
인기 있는 '브랜드' Entity

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싸이퍼 예시
데이터 재구성
MATCH (:Tag {name:'브랜드'})<--(e:Entity)<--(t:Topic)<--(q:Query)-[r:RELEVANT]->(p:Product)
WITH p, q, t, e
ORDER BY e.qc DESC, t.qc DESC, q.qc DESC, r.score DESC
WITH collect(DISTINCT p) AS product_list, collect(DISTINCT q) AS query_list, collect(DISTINC
T t) AS topic_list, e
UNWIND product_list[0] AS p
UNWIND query_list[0] AS q
UNWIND topic_list[0] AS t
RETURN e.entity AS Entity, p.prod_nm AS Product_Name
LIMIT 10
UNWIND expands a list into a sequence of rows.
인기 있는 브랜드 Entity를 조회한 후, 해당 Entity의 인기 상품이 무엇인지

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싸이퍼 예시
데이터 재구성
MATCH (q:Query)-[r:RELEVANT]->(p:Product)<--(c:Category)
WHERE q.query =~ '.*선물(추천)?$'
RETURN c.cat_name AS Category, sum(q.qc) AS QC, collect(DISTINCT q.query) AS Query
ORDER BY QC DESC
LIMIT 10
선물로 인기 있는 카테고리가 어떤 것이 있는지

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시연
Neo4j AuraDB
https://console.neo4j.io

18. Thank you.
[출처]
위키백과
NAVER D2
couplewith 티스토리