Konstantinos Markellos, P. Markellou, A. L. Tsakalidi, Marina Staurianoudaki
{"title":"农业领域的个性化网络服务:向农民和种植者推荐有机种子的案例研究","authors":"Konstantinos Markellos, P. Markellou, A. L. Tsakalidi, Marina Staurianoudaki","doi":"10.1504/IJED.2009.028545","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce RecOrgSeed, a model for producing interesting recommendations to organic farmers/growers. The whole process has been distinguished into two stages, one off-line that includes data preparation, ontology creation and usage mining and one online that concerns the recommendations production. The knowledge about farmers/growers (users) and seeds (products) is extracted from usage mining data and semantic annotations in conjunction with user-product ratings and matching techniques between users. The preliminary evaluation experiments show that even in the case of \"cold-start problem\" where no initial behavioural information is available, the approach can provide users with logical and relevant recommendations.","PeriodicalId":141497,"journal":{"name":"International Journal of Electronic Democracy","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Personalised web services for agricultural domain: a case study for recommending organic seeds to farmers and growers\",\"authors\":\"Konstantinos Markellos, P. Markellou, A. L. Tsakalidi, Marina Staurianoudaki\",\"doi\":\"10.1504/IJED.2009.028545\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce RecOrgSeed, a model for producing interesting recommendations to organic farmers/growers. The whole process has been distinguished into two stages, one off-line that includes data preparation, ontology creation and usage mining and one online that concerns the recommendations production. The knowledge about farmers/growers (users) and seeds (products) is extracted from usage mining data and semantic annotations in conjunction with user-product ratings and matching techniques between users. The preliminary evaluation experiments show that even in the case of \\\"cold-start problem\\\" where no initial behavioural information is available, the approach can provide users with logical and relevant recommendations.\",\"PeriodicalId\":141497,\"journal\":{\"name\":\"International Journal of Electronic Democracy\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Electronic Democracy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJED.2009.028545\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Electronic Democracy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJED.2009.028545","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Personalised web services for agricultural domain: a case study for recommending organic seeds to farmers and growers
In this paper, we introduce RecOrgSeed, a model for producing interesting recommendations to organic farmers/growers. The whole process has been distinguished into two stages, one off-line that includes data preparation, ontology creation and usage mining and one online that concerns the recommendations production. The knowledge about farmers/growers (users) and seeds (products) is extracted from usage mining data and semantic annotations in conjunction with user-product ratings and matching techniques between users. The preliminary evaluation experiments show that even in the case of "cold-start problem" where no initial behavioural information is available, the approach can provide users with logical and relevant recommendations.