个性化推荐算法的自适应框架

Proceedings of 2014 International Conference on Cloud Computing and Internet of Things Pub Date : 2014-12-01 DOI:10.1109/CCIOT.2014.7062515

Jianchang Tang, Xinhuai Tang

{"title":"个性化推荐算法的自适应框架","authors":"Jianchang Tang, Xinhuai Tang","doi":"10.1109/CCIOT.2014.7062515","DOIUrl":null,"url":null,"abstract":"Different personalized recommendation algorithms are suitable for different scenarios. In this paper, we use artificial neural networks to implement an adaptive framework. When we add different recommendation algorithms into it and train it with the data from a given scenario, it can calculate the weight of each algorithm, choose suitable algorithms and give a more accurate prediction rating.","PeriodicalId":255477,"journal":{"name":"Proceedings of 2014 International Conference on Cloud Computing and Internet of Things","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An adaptive framework for personalized recommendation algorithms\",\"authors\":\"Jianchang Tang, Xinhuai Tang\",\"doi\":\"10.1109/CCIOT.2014.7062515\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Different personalized recommendation algorithms are suitable for different scenarios. In this paper, we use artificial neural networks to implement an adaptive framework. When we add different recommendation algorithms into it and train it with the data from a given scenario, it can calculate the weight of each algorithm, choose suitable algorithms and give a more accurate prediction rating.\",\"PeriodicalId\":255477,\"journal\":{\"name\":\"Proceedings of 2014 International Conference on Cloud Computing and Internet of Things\",\"volume\":\"87 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2014 International Conference on Cloud Computing and Internet of Things\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCIOT.2014.7062515\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2014 International Conference on Cloud Computing and Internet of Things","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCIOT.2014.7062515","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

不同的个性化推荐算法适用于不同的场景。在本文中，我们使用人工神经网络来实现一个自适应框架。当我们加入不同的推荐算法，并使用给定场景的数据对其进行训练时，它可以计算出每种算法的权重，选择合适的算法，给出更准确的预测评级。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

An adaptive framework for personalized recommendation algorithms

Different personalized recommendation algorithms are suitable for different scenarios. In this paper, we use artificial neural networks to implement an adaptive framework. When we add different recommendation algorithms into it and train it with the data from a given scenario, it can calculate the weight of each algorithm, choose suitable algorithms and give a more accurate prediction rating.

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

Proceedings of 2014 International Conference on Cloud Computing and Internet of Things

自引率

0.00%

发文量