A multi-label ensemble predicting model to service recommendation from social media contents
Author:
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11227-021-04087-7.pdf
Reference44 articles.
1. Siering M, Deokar AV, Janze C (2018) Disentangling consumer recommendations: explaining and predicting airline recommendations based on online reviews. Decis Support Syst 107:52–63
2. Sezgen E, Mason KJ, Mayer R (2019) Voice of airline passenger: a text mining approach to understand customer satisfaction. J Air Transp Manag 77:65–74
3. Guan Y, Wei Q, Chen G (2019) Deep learning based personalized recommendation with multi-view information integration. Decis Support Syst 118:58–69
4. Koehn D, Lessmann S, Schaal M (2020) Predicting online shopping behaviour from clickstream data using deep learning. Expert Syst Appl 150:113342
5. Kumar A et al (2019) Combined artificial bee colony algorithm and machine learning techniques for prediction of online consumer repurchase intention. Neural Comput Appl 312:877–890
Cited by 28 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. The asymmetric impact of Twitter Sentiment and emotions: Impulse response analysis on European tourism firms using micro-data;Tourism Management;2024-10
2. Enhancing Community E-Commerce Repurchase Prediction Through Information Entropy Analysis;International Journal of e-Collaboration;2024-07-30
3. Machine learning applied to tourism: A systematic review;WIREs Data Mining and Knowledge Discovery;2024-07-04
4. Semantic features analysis for biomedical lexical answer type prediction using ensemble learning approach;Knowledge and Information Systems;2024-04-25
5. Social network based link correlation using graph neural network with deep learning architectures for feature vectors prediction and classification;Concurrency and Computation: Practice and Experience;2024-04-10
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