This is for the knowledge graph embedding recommendation framework – RKGE
Source code for KDD 2018 paper "Leverage Meta-path based Context for Top-N Recommendation with a Neural Co-Attention Model"
:red_car: The 1st Place Submission to AICity Challenge 2020 re-id track (Baidu-UTS submission)
A tutorial and implement of disease centered Medical knowledge graph and qa system based on it。知识图谱构建,自动问答,基于kg的自动问答。以疾病为中心的一定规模医药领域知识图谱,并以该知识图谱完成自动问答与分析服务。
Python Implementation of Probabilistic Matrix Factorization(PMF) Algorithm for building a recommendation system using MovieLens ml-100k | GroupLens dataset
由时间空间成对组成的轨迹序列,通过循环神经网络lstm,自编码器auto-encode,时空密度聚类st-dbscan做异常检测
一个基于 fasttext + faiss 的商品内容相关推荐实现,nginx+uwsgi+flask / gunicorn+uvicorn+fastapi 提供api查询接口,增加Spark实现 Ansj+Word2vec+LSH+Phoenix
商品大数据实时推荐系统。前端:Vue + TypeScript + ElementUI,后端 Spring + Spark
:whale:基于 Flink 的商品实时推荐系统。当用户产生评分行为时,数据由 kafka 发送到 flink,根据用户历史评分行为进行实时和离线推荐。实时推荐包括:基于行为和实时热门,离线推荐包括:历史热门、历史优质商品和 itemcf 。
Simple Tensorflow Implementation of "A Structured Self-attentive Sentence Embedding" (ICLR 2017)