{"title":"协同上下文预测的一种方法","authors":"Christian Voigtmann, Sian Lun Lau, K. David","doi":"10.1109/PERCOMW.2011.5766929","DOIUrl":null,"url":null,"abstract":"Context prediction approaches forecast future contexts based on known context patterns to adapt e.g., services in advance. In the case of the user's context history not providing suitable context information for the observed context pattern, to the best of our knowledge context prediction algorithms will fail to forecast the appropriate future context. To overcome the gap of missing context information in the user's context history, we propose the Collaborative Context Prediction (CCP) approach. CCP utilises the collaborative characteristics of existing recommendation systems of social networks. To evaluate the CCP method an experimental comparison of the proposed method against the local Alignment context predictor is carried out.","PeriodicalId":369430,"journal":{"name":"2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"An approach to Collaborative Context Prediction\",\"authors\":\"Christian Voigtmann, Sian Lun Lau, K. David\",\"doi\":\"10.1109/PERCOMW.2011.5766929\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Context prediction approaches forecast future contexts based on known context patterns to adapt e.g., services in advance. In the case of the user's context history not providing suitable context information for the observed context pattern, to the best of our knowledge context prediction algorithms will fail to forecast the appropriate future context. To overcome the gap of missing context information in the user's context history, we propose the Collaborative Context Prediction (CCP) approach. CCP utilises the collaborative characteristics of existing recommendation systems of social networks. To evaluate the CCP method an experimental comparison of the proposed method against the local Alignment context predictor is carried out.\",\"PeriodicalId\":369430,\"journal\":{\"name\":\"2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PERCOMW.2011.5766929\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PERCOMW.2011.5766929","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Context prediction approaches forecast future contexts based on known context patterns to adapt e.g., services in advance. In the case of the user's context history not providing suitable context information for the observed context pattern, to the best of our knowledge context prediction algorithms will fail to forecast the appropriate future context. To overcome the gap of missing context information in the user's context history, we propose the Collaborative Context Prediction (CCP) approach. CCP utilises the collaborative characteristics of existing recommendation systems of social networks. To evaluate the CCP method an experimental comparison of the proposed method against the local Alignment context predictor is carried out.