array(4) { [0]=> string(35) "survey1/News recommender_October 14" [1]=> string(16) " 2023_12.50.xlsx" [2]=> string(5) "20016" [3]=> string(21) "2023-10-15 15:08:42 " } MINDFUL-A-Lenskit-based-Recommender-System 联合开发网 - pudn.com
MINDFUL-A-Lenskit-based-Recommender-System

所属分类:代码编辑器
开发工具:Jupyter Notebook
文件大小:0KB
下载次数:0
上传日期:2023-10-09 20:36:27
上 传 者sh-1993
说明:  一个协作小组项目,旨在使用MIND(MIcrosoft新闻数据集)数据集和Pytho...开发强大的推荐系统...,
(a collaborative group project aimed at developing a powerful recommender system using the MIND (MIcrosoft News Dataset) dataset and Python Lenskit recommendation engine.)

文件列表:
.idea/ (0, 2023-10-15)
.ipynb_checkpoints/ (0, 2023-10-15)
.ipynb_checkpoints/Untitled-checkpoint.ipynb (10913, 2023-10-15)
.ipynb_checkpoints/for_groups-checkpoint.ipynb (12576, 2023-10-15)
.ipynb_checkpoints/group_recommendation_added-checkpoint.ipynb (38286, 2023-10-15)
.ipynb_checkpoints/mega_clean_model-checkpoint.ipynb (134055, 2023-10-15)
.ipynb_checkpoints/surveydat-checkpoint.ipynb (43856, 2023-10-15)
LICENSE (1069, 2023-10-15)
Recommendations based on the MIND News Dataset.pptx (3977509, 2023-10-15)
for_groups.ipynb (1161729, 2023-10-15)
group_recommendation_added.ipynb (39265, 2023-10-15)
grouped_dict.json (28047, 2023-10-15)
mega_clean_model.ipynb (134055, 2023-10-15)
small_test_data/ (0, 2023-10-15)
small_test_data/behaviors.tsv (42838544, 2023-10-15)
small_test_data/entity_embedding.vec (21960998, 2023-10-15)
small_test_data/news.tsv (33519092, 2023-10-15)
small_test_data/relation_embedding.vec (1044588, 2023-10-15)
small_training_data/ (0, 2023-10-15)
small_training_data/behaviors.tsv (92019716, 2023-10-15)
small_training_data/entity_embedding.vec (25811015, 2023-10-15)
small_training_data/news.tsv (41202121, 2023-10-15)
small_training_data/relation_embedding.vec (1044588, 2023-10-15)
survey1/ (0, 2023-10-15)
survey1/Recsys Group Project Survey 1 questions.xlsx (13149, 2023-10-15)
surveydat.ipynb (43856, 2023-10-15)
unique_users.pkl (48310060, 2023-10-15)
userBOW.pkl (3946587, 2023-10-15)

# Group 9 # MINDFUL-A-Lenskit-based-Recommender-System A collaborative group project aimed at developing a powerful recommender system using the MIND (MIcrosoft News Dataset) dataset and Python Lenskit recommendation engine.

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