Alec A. Souders, Mohammad S. Almalag, Christopher Kreider
{"title":"个性化路线导航系统:利用可用的静态和实时数据进行基于偏好的推荐","authors":"Alec A. Souders, Mohammad S. Almalag, Christopher Kreider","doi":"10.1109/gcaiot53516.2021.9692993","DOIUrl":null,"url":null,"abstract":"Efficiency has become an extremely important factor in route navigation applications. Many systems offer the fastest route possible to a destination by using information including traffic data, road construction status, and more. However, many existing route navigation systems significantly lack the ability to account for personalized user information. The goal of this research was to develop a personalized route navigation algorithm capable of indexing routes classified by a user’s estimated satisfaction, considering relevant information provided from previous studies, without the need for external hardware or sensors. Said routes produced by the end-goal system are constructed and indexed using available live and static data from external resources.","PeriodicalId":169247,"journal":{"name":"2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)","volume":"363 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Personalized Route Navigation System: Utilizing Available Static and Live Data for Preference-Based Recommendation\",\"authors\":\"Alec A. Souders, Mohammad S. Almalag, Christopher Kreider\",\"doi\":\"10.1109/gcaiot53516.2021.9692993\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Efficiency has become an extremely important factor in route navigation applications. Many systems offer the fastest route possible to a destination by using information including traffic data, road construction status, and more. However, many existing route navigation systems significantly lack the ability to account for personalized user information. The goal of this research was to develop a personalized route navigation algorithm capable of indexing routes classified by a user’s estimated satisfaction, considering relevant information provided from previous studies, without the need for external hardware or sensors. Said routes produced by the end-goal system are constructed and indexed using available live and static data from external resources.\",\"PeriodicalId\":169247,\"journal\":{\"name\":\"2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)\",\"volume\":\"363 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/gcaiot53516.2021.9692993\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/gcaiot53516.2021.9692993","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Personalized Route Navigation System: Utilizing Available Static and Live Data for Preference-Based Recommendation
Efficiency has become an extremely important factor in route navigation applications. Many systems offer the fastest route possible to a destination by using information including traffic data, road construction status, and more. However, many existing route navigation systems significantly lack the ability to account for personalized user information. The goal of this research was to develop a personalized route navigation algorithm capable of indexing routes classified by a user’s estimated satisfaction, considering relevant information provided from previous studies, without the need for external hardware or sensors. Said routes produced by the end-goal system are constructed and indexed using available live and static data from external resources.