Spring Batch 기반의 추천 시스템 로직 구현#21
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PR 타입
구현한 기능
Step 1. 활동 CTR 계산 - 활동별 클릭률(CTR)을 계산하여 저장
Step 2. 상위 활동 순위화 - CTR 기준 상위 활동을 activity_ranking에 저장
Step 3. 사용자 선호 임베딩 갱신 - 사용자의 선호 키워드를 바탕으로 임베딩 벡터 계산 및 저장
Step 4. 활동 평균 임베딩 갱신 - 각 활동의 사용자 평점 기반 평균 임베딩 계산
Step 5. 사용자-활동 그래프 간선 갱신 - 임베딩 기반으로 :PREFERRED, :SIMILAR 간선 갱신 (Neo4j)
Step 6. 낮은 점수 간선 제거 - 임계값 이하의 관계 간선 제거
Step 7. 최종 추천 리스트 저장 - 계산된 추천 활동 리스트를 사용자별로 DB에 저장
테스트 결과
일정