{"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。
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.