PERSONALIZED

作品数：385被引量：642H指数：11
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Acute Complication Prediction and Diagnosis Model CLSTM-BPR:A Fusion Method of Time Series Deep Learning and Bayesian Personalized Ranking
《Tsinghua Science and Technology》2024年第5期1509-1523,共15页Xi Chen Quan Cheng 
supported by the Social Science Fund of China(No.19BTQ072).
Acute complication prediction model is of great importance for the overall reduction of premature death in chronic diseases.The CLSTM-BPR proposed in this paper aims to improve the accuracy,interpretability,and genera...
关键词：Long Short-Term Memory(LSTM) Bayesian Personalized Ranking(BPR) sudden illnesses disease predictions 
Federated Meta Reinforcement Learning for Personalized Tasks
《Tsinghua Science and Technology》2024年第3期911-926,共16页Wentao Liu Xiaolong Xu Jintao Wu Jielin Jiang 
supported by the National Key Research and Development Program of China(No.2020YFB1707601);the Major Research Plan of the National Natural Science Foundation of China(No.92267104);the Natural Science Foundation of Jiangsu Province of China(No.BK20211284);the Financial and Science Technology Plan Project of Xinjiang Production and Construction Corps(No.2020DB005).
As an emerging privacy-preservation machine learning framework,Federated Learning(FL)facilitates different clients to train a shared model collaboratively through exchanging and aggregating model parameters while raw ...
关键词：federated learning reinforcement learning META-LEARNING PERSONALIZATION 
Preserving Personalized Location Privacy in Ride-Hailing Service被引量：6
《Tsinghua Science and Technology》2020年第6期743-757,共15页Youssef Khazbak Jingyao Fan Sencun Zhu Guohong Cao 
Ride-hailing service has become a popular means of transportation due to its convenience and low cost.However,it also raises privacy concerns.Since riders’mobility information including the pick-up and drop-off locat...
关键词：ride-hailing location privacy privacy preserving Voronoi diagram 
Personalized Real-Time Movie Recommendation System:Practical Prototype and Evaluation被引量：18
《Tsinghua Science and Technology》2020年第2期180-191,共12页Jiang Zhang Yufeng Wang Zhiyuan Yuan Qun Jin 
With the eruption of big data,practical recommendation schemes are now very important in various fields,including e-commerce,social networks,and a number of web-based services.Nowadays,there exist many personalized mo...
关键词：movie recommendation system collaborative filtering REAL-TIME virtual opinion leader data mining 
Architecture of Next-Generation E-Commerce Platform被引量：4
《Tsinghua Science and Technology》2019年第1期18-29,共12页Yadong Huang Yueting Chai Yi Liu Jianping Shen 
supported by the National Key Research and Development Plan of China:Research on Fundamental Theories and Methods of Crowd Science(No.2017YFB1400100)
E-commerce, driven by computer and internet technology, has experienced a significant growth in almost all fields during the past two decades. E-commerce has significantly changed the rules of business. Numerous resea...
关键词：e-commerce PERSONALIZED PORTAL accurate demand reliable supply smart CYBERSPACE 
Personalized Cranium Defects Restoration Technique Based on Reverse Engineering被引量：2
《Tsinghua Science and Technology》2009年第S1期82-88,共7页付红圣 高亮 鞠鲁粤 刘俞章 
The purpose of this paper is to overcome the limitations of the traditional cranial defects restoration technique and better satisfy the aesthetic and comfort demands of different patients. An arithmetic profile curve...
关键词：computer tomography (CT) blending arithmetic CRANIOPLASTY reverse engineering multiple-point forming (MPF) 
Personalized Multi-View Face Animation with Lifelike Textures
《Tsinghua Science and Technology》2007年第1期51-57,共7页柳杨华 徐光祐 
the National Natural Science Foundation of China (No. 60673189)
Realistic personalized face animation mainly depends on a picture-perfect appearance and natural head rotation. This paper describes a face model for generation of novel view facial textures with various realistic exp...
关键词：face animation point distribution model （PDM） TEXTURE MULTI-VIEW 
User Modeling for Personalized Recommender Systems
《Tsinghua Science and Technology》2005年第z1期772-777,共6页LIU Lu WU Lihua 
Supported by the National Natural Science Foundation of China (No. 70371004); the Ph. D. Program Foundation of the Ministry of Education, China ( No. 20040006023)
This paper models a user's interest and value related characteristics based on the extension by using neural networks and econometric techniques to the concept of user model in recommender systems. A two-dimensional t...
关键词：user INTEREST model CUSTOMER LIFETIME value (CLV) RECOMMENDER systems CUSTOMER relationship management (CRM) e-commerce 
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