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meta_recommend's Introduction

environment

  • version
    • gensim

code

  1. save_json_fashion.py
  • raw data 에서 전처리를 커쳐 input 을 json 형태로 저장합니다. (save name 설정 필요)
  1. doc2vec_fashion.py
  • doc2vec 을 사용하기 위한 모델 설계
  • doc2vec 모델 weight 저장 (path 설정)
  • 학습된 결과를 통해 topk 개의 추천 list 를 저장
  1. inference_fashion.py
# json : input query json file
# metadata : training model metadata (for recommend in it)
# model : trained doc2vec model
# topk : return item num
python doc2vec_fashion.py --json example_jsonfile.json --metadata metadata.json --model doc2vec_model --topk 5 
  • input
    • raw data 의 메타 정보
    • 학습된 모델의 메타정보 json file
    • 학습된 doc2vec 모델
    • 추천될 topk 수
  • 예시
    • input_list = ['셔츠', ''셔츠칼라'', ''루즈'', ''체크'','스커트','롱','데님']

    • output

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Contributors

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