A Deep Hybrid Model for Recommendation by jointly leveraging ratings, reviews and metadata information-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A Deep Hybrid Model for Recommendation by jointly leveraging ratings, reviews and metadata information

Published:2021-01 Issue: Volume:97 Page:104066
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Khan Zahid Younas,Niu Zhendong,Nyamawe Ally S.,Haq Ijaz ul

Funder

National Key R&D Program of China

National Natural Science Foundation of China

National Basic Research Program of China

Ministry of Education - China Mobile Research Foundation Project

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference37 articles.

1. Regression model to predict global solar irradiance in Malaysia;Ahmed Kutty;Int. J. Photoenergy,2015

2. TopicMF: Simultaneously exploiting ratings and reviews for recommendation;Bao,2014

3. Latent Dirichlet allocation;Blei;J. Mach. Learn. Res.,2003

4. TransNets: Learning to transform for recommendation;Catherine,2017

5. Review text based rating prediction approaches: preference knowledge learning, representation and utilization;Chambua;Artif. Intell. Rev.,2020

Cited by 20 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A deep feature interaction and fusion model for fake review detection: Advocating heterogeneous graph convolutional network;Neurocomputing;2024-09

2. CNNRec: Convolutional Neural Network based recommender systems - A survey;Engineering Applications of Artificial Intelligence;2024-07

3. Application Analysis of Generative Artificial Intelligence in The field of Open Source Intelligence;2024 39th Youth Academic Annual Conference of Chinese Association of Automation (YAC);2024-06-07

4. An automated machine learning approach for detecting anomalous peak patterns in time series data from a research watershed in the northeastern United States critical zone;Machine Learning with Applications;2024-06

5. Fake review detection techniques, issues, and future research directions: a literature review;Knowledge and Information Systems;2024-05-17

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3