2026数据科学与大数据技术一套基于神经网络的计算机图书推荐与分析系统3.67-AI9.83(论文+程序代码源码+运行指导.md)定稿.zip

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2026-09-18
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收起资源包目录

bdu26bd244zhangyuyangbooks_recommend_system
- bdu26bd244zhangyuyangclawer
  - run244zhangyuyang.py(5.79 KB)
  - 爬取网址.txt(114 B)
- bdu26bd244zhangyuyangconfig
  - config.yaml(466 B)
- bdu26bd244zhangyuyangdata
  - clean
    - cleaned.csv(2.8 MB)
    - cleaned.xlsx(1.07 MB)
  - out
    - analysis_01_topic_quality_landscape
      - recent_topic_rank.csv(411 B)
      - topic_summary.csv(1.43 KB)
      - topic_year_stats.csv(9.97 KB)
    - analysis_02_content_similarity_prepare
      - book_vectors.csv(1.09 MB)
      - prep_metrics.csv(41 B)
      - vocabulary_preview.csv(2 KB)
    - analysis_03_learning_cost_effectiveness
      - high_value_books.csv(8.08 KB)
      - topic_cost_overview.csv(1.25 KB)
      - topic_year_cost_trend.csv(10.66 KB)
    - analysis_04_publisher_author_supply
      - author_influence_rank.csv(3.62 KB)
      - press_influence_rank.csv(2.84 KB)
      - press_topic_coverage.csv(3.31 KB)
    - analysis_05_rating_sentiment_structure
      - consensus_books.csv(3.1 KB)
      - controversial_books.csv(3.13 KB)
      - topic_reputation_profile.csv(676 B)
    - analysis_06_popularity_drivers_ml
      - book_popularity_prediction.csv(163.47 KB)
      - model_metrics.csv(81 B)
      - popularity_feature_importance.csv(2.44 KB)
      - topic_popularity_residual.csv(692 B)
  - raw
    - biancheng_books.csv(577.1 KB)
    - jisuanji_books.csv(1.5 MB)
- bdu26bd244zhangyuyangdocs
  - model_evaluation_report.md(7.15 KB)
  - recommender.md(1.01 KB)
  - web_dashboard_handover.md(8.82 KB)
  - 数据集清洗规则.md(2.6 KB)
  - 评估结果.md(1.51 KB)
- bdu26bd244zhangyuyangmodels
  - bdu26bd244zhangyuyangrecommender
    - autoencoder.pt(1.32 MB)
    - autoencoder.pt.meta.json(68 B)
    - books.faiss(257.04 KB)
    - book_embeddings.npy(2.01 MB)
    - book_meta.parquet(1.44 MB)
    - latent_vectors.npy(257.13 KB)
    - prepared_books.parquet(1.42 MB)
- bdu26bd244zhangyuyangrecommender
  - autoencoder244zhangyuyang.py(907 B)
  - build_index244zhangyuyang.py(2.07 KB)
  - config244zhangyuyang.py(1.56 KB)
  - data244zhangyuyang.py(2.54 KB)
  - embedding244zhangyuyang.py(1.45 KB)
  - network244zhangyuyang.py(835 B)
  - prepare_books244zhangyuyang.py(720 B)
  - search244zhangyuyang.py(4.21 KB)
  - train_autoencoder244zhangyuyang.py(2.83 KB)
  - utils244zhangyuyang.py(2.04 KB)
  - __init__.py(37 B)
- bdu26bd244zhangyuyangscripts
  - reduce_similarity_map244zhangyuyang.py(5.16 KB)
- bdu26bd244zhangyuyangsh
  - export_all_analysis244zhangyuyang.sh(6.22 KB)
  - run_all_analyses244zhangyuyang.sh(1.88 KB)
  - run_clean_books244zhangyuyang.sh(1.26 KB)
- bdu26bd244zhangyuyangspark_jobs
  - analysis_01_topic_quality_landscape244zhangyuyang.py(5.69 KB)
  - analysis_02_content_clusters244zhangyuyang.py(6.28 KB)
  - analysis_02_content_similarity_prepare244zhangyuyang.py(5.87 KB)
  - analysis_03_learning_cost_effectiveness244zhangyuyang.py(5.02 KB)
  - analysis_04_publisher_author_supply244zhangyuyang.py(4.65 KB)
  - analysis_05_rating_sentiment_structure244zhangyuyang.py(4.9 KB)
  - analysis_06_popularity_drivers_ml244zhangyuyang.py(9.44 KB)
  - analysis_common244zhangyuyang.py(2.5 KB)
  - step1_clean_books244zhangyuyang.py(6.04 KB)
- bdu26bd244zhangyuyangweb
  - css
    - hub244zhangyuyang.css(3.61 KB)
    - page244zhangyuyang.css(9.46 KB)
    - reset244zhangyuyang.css(3.3 KB)
  - images
    - logo.jpg(1.77 KB)
  - js
    - data-utils244zhangyuyang.js(8.45 KB)
    - index244zhangyuyang.js(28.38 KB)
    - jquery.min.js(93.58 KB)
    - jquery.nicescroll.min.js(58.6 KB)
    - topic-pages244zhangyuyang.js(13.37 KB)
  - laydate
    - theme
      - default
        font
        iconfont.ttf(84 B)
        iconfont.woff(84 B)
        laydate.css(7.79 KB)
    - laydate.js(26.74 KB)
  - advanced244zhangyuyang.html(3.17 KB)
  - content244zhangyuyang.html(2.2 KB)
  - index244zhangyuyang.html(2.02 KB)
  - overview244zhangyuyang.html(6.58 KB)
  - traditional244zhangyuyang.html(2.95 KB)
- app_streamlit244zhangyuyang.py(14.75 KB)
- requirements.txt(311 B)
bdu26bd244zhangyuyangbooks_spark
- .git
  - hooks
    - applypatch-msg.sample(478 B)
    - commit-msg.sample(896 B)
    - fsmonitor-watchman.sample(4.62 KB)
    - post-update.sample(189 B)
    - pre-applypatch.sample(424 B)
    - pre-commit.sample(1.61 KB)
    - pre-merge-commit.sample(416 B)
    - pre-push.sample(1.34 KB)
    - pre-rebase.sample(4.78 KB)
    - pre-receive.sample(544 B)
    - prepare-commit-msg.sample(1.46 KB)
    - push-to-checkout.sample(2.72 KB)
    - sendemail-validate.sample(2.25 KB)
    - update.sample(3.56 KB)
  - info
    - exclude(240 B)
  - logs
    - refs
      - heads
        main(632 B)
    - HEAD(830 B)
  - objects
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    - info
    - pack
  - refs
    - heads
      - main(41 B)
    - tags
  - COMMIT_EDITMSG(18 B)
  - config(130 B)
  - description(73 B)
  - HEAD(41 B)
  - index(8.93 KB)
- bdu26bd244zhangyuyangclawer
  - run244zhangyuyang.py(5.79 KB)
  - 爬取网址.txt(114 B)
- bdu26bd244zhangyuyangdata
  - clean
    - cleaned.csv(2.8 MB)
    - cleaned.xlsx(1.07 MB)
  - out
    - analysis_01_topic_quality_landscape
      - recent_topic_rank.csv(411 B)
      - topic_summary.csv(1.43 KB)
      - topic_year_stats.csv(9.97 KB)
    - analysis_02_content_similarity_prepare
      - book_vectors.csv(1.09 MB)
      - prep_metrics.csv(41 B)
      - vocabulary_preview.csv(2 KB)
    - analysis_03_learning_cost_effectiveness
      - high_value_books.csv(8.08 KB)
      - topic_cost_overview.csv(1.25 KB)
      - topic_year_cost_trend.csv(10.66 KB)
    - analysis_04_publisher_author_supply
      - author_influence_rank.csv(3.62 KB)
      - press_influence_rank.csv(2.84 KB)
      - press_topic_coverage.csv(3.31 KB)
    - analysis_05_rating_sentiment_structure
      - consensus_books.csv(3.1 KB)
      - controversial_books.csv(3.13 KB)
      - topic_reputation_profile.csv(676 B)
    - analysis_06_popularity_drivers_ml
      - book_popularity_prediction.csv(163.47 KB)
      - model_metrics.csv(81 B)
      - popularity_feature_importance.csv(2.44 KB)
      - topic_popularity_residual.csv(692 B)
  - raw
    - biancheng_books.csv(577.1 KB)
    - jisuanji_books.csv(1.5 MB)
- bdu26bd244zhangyuyangmodels
  - bdu26bd244zhangyuyangrecommender
    - autoencoder.pt(1.32 MB)
    - autoencoder.pt.meta.json(68 B)
    - books.faiss(257.04 KB)
    - book_embeddings.npy(2.01 MB)
    - book_meta.parquet(1.44 MB)
    - latent_vectors.npy(257.13 KB)
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  - analysis_06_popularity_drivers_ml244zhangyuyang.py(9.44 KB)
  - analysis_common244zhangyuyang.py(2.5 KB)
  - step1_clean_books244zhangyuyang.py(6.04 KB)
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- config.yaml(466 B)
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2026数据科学与大数据技术一套基于神经网络的计算机图书推荐与分析系统3.67-AI9.83(论文+程序代码源码+运行指导.md)定稿.zip