Time-aware personalized ranking for sequential item recommendation

碩士 === 國立臺灣大學 === 資訊工程學研究所 === 104 === In this thesis, we aim at building a recommender system for sequential data. The goal is to predict a user’s next action based on his or her last basket of actions. In order to solve this task, FPMC is proposed by Rendle to model both sequential behavior and us...

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Bibliographic Details
Main Authors: Pei-Xun Wang, 王珮恂
Other Authors: Shou-De Lin
Format: Others
Language:en_US
Published: 2016
Online Access:http://ndltd.ncl.edu.tw/handle/11824387368954349442