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A Comparative Framework for Multimodal Recommender Systems

Jstarcraft Rns ⭐ 368

专注于解决推荐领域与搜索领域的两个核心问题:排序预测(Ranking)和评分预测(Rating). 为相关领域的研发人员提供完整的通用设计与参考实现. 涵盖了70多种排序预测与评分预测算法,是最快最全的Java推荐与搜索引擎.

Www2018_lrml ⭐ 31

Implementation of "Latent Relational Metric Learning via Memory-based Attention for Collaborative Ranking"

Ranking-Critical Training for Collaborative Filtering

Neural_social_collaborative_ranking ⭐ 23

Item Silk Road: Recommending Items from Information Domains to Social Users, SIGIR2017

Datascienceprojects ⭐ 17

Sample data science projects (machine learning, optimization, business intelligence)

Cleverrec ⭐ 11

CleverRec: An Open-source Toolkit for Recommendation System.

New algorithms for Large-scale Collaborative Ranking: PrimalCR and PrimalCR++

Sql Rank ⭐ 10

A Novel Listwise Collaborative Ranking Algorithm published at ICML'18

C++ implementation of primalCR and primalCR++ proposed in KDD'17 paper

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