基于k -均值聚类和ARIMAX模型的JXM游戏下一个购买项目预测

Thien Nguyen, Thanh Le, Bac Le
{"title":"基于k -均值聚类和ARIMAX模型的JXM游戏下一个购买项目预测","authors":"Thien Nguyen, Thanh Le, Bac Le","doi":"10.1109/NICS51282.2020.9335839","DOIUrl":null,"url":null,"abstract":"This paper is instructions for how to predict 5 next purchase items in “Vo Lam Truyen Ky Mobile” (JXM) which is a VNG's hot game. It's so hard to predict the next purchase item with a massive number of transactions per day. So, we analysed data to establish the solution to this problem. The solution make a prediction based on the past purchasing and in-game data with K-Means Clustering and ARIMAX model reaching accuracy about 70 percent. The research result can help to recommend items fit with users, improve user experience and may increase revenue.","PeriodicalId":308944,"journal":{"name":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Predicting Next Purchase Item on JXM Game by K-Means Clustering and ARIMAX Model\",\"authors\":\"Thien Nguyen, Thanh Le, Bac Le\",\"doi\":\"10.1109/NICS51282.2020.9335839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper is instructions for how to predict 5 next purchase items in “Vo Lam Truyen Ky Mobile” (JXM) which is a VNG's hot game. It's so hard to predict the next purchase item with a massive number of transactions per day. So, we analysed data to establish the solution to this problem. The solution make a prediction based on the past purchasing and in-game data with K-Means Clustering and ARIMAX model reaching accuracy about 70 percent. The research result can help to recommend items fit with users, improve user experience and may increase revenue.\",\"PeriodicalId\":308944,\"journal\":{\"name\":\"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NICS51282.2020.9335839\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 7th NAFOSTED Conference on Information and Computer Science (NICS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NICS51282.2020.9335839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

本文是关于如何预测VNG热门游戏《武林Truyen Ky Mobile》(JXM)下一个购买项目的说明。每天都有大量的交易,很难预测下一个购买项目。因此,我们通过分析数据来建立这个问题的解决方案。该方案利用K-Means聚类和ARIMAX模型对过去的购买和游戏数据进行预测,准确率约为70%。研究结果可以帮助推荐适合用户的商品,改善用户体验,并可能增加收入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting Next Purchase Item on JXM Game by K-Means Clustering and ARIMAX Model
This paper is instructions for how to predict 5 next purchase items in “Vo Lam Truyen Ky Mobile” (JXM) which is a VNG's hot game. It's so hard to predict the next purchase item with a massive number of transactions per day. So, we analysed data to establish the solution to this problem. The solution make a prediction based on the past purchasing and in-game data with K-Means Clustering and ARIMAX model reaching accuracy about 70 percent. The research result can help to recommend items fit with users, improve user experience and may increase revenue.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信