André Abdalla, Victor Ströele, Fernanda Campos, J. M. David, Regina M. M. Braga
{"title":"Software Ecosystem Platform for Recommendation Systems","authors":"André Abdalla, Victor Ströele, Fernanda Campos, J. M. David, Regina M. M. Braga","doi":"10.1145/3229345.3229418","DOIUrl":null,"url":null,"abstract":"The need to recommend resources in many different application domains and to develop solutions focused on recommender systems (RS) components reuse create an interesting scenario for the adoption of Software Ecosystem (SECO) perspective. In this way, the problem addressed by this study is how to integrate the various methods of existing recommendation systems in a systematic and centralized way. This paper proposes R.ECOS, a reuse-based ecosystem platform for RS. The proposal evaluation was carried out through a case study. The results point to the solution feasibility, along with the platform components. The main contribution is the implementation of the platform that supports the proposed SECO.","PeriodicalId":284178,"journal":{"name":"Proceedings of the XIV Brazilian Symposium on Information Systems","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the XIV Brazilian Symposium on Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3229345.3229418","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The need to recommend resources in many different application domains and to develop solutions focused on recommender systems (RS) components reuse create an interesting scenario for the adoption of Software Ecosystem (SECO) perspective. In this way, the problem addressed by this study is how to integrate the various methods of existing recommendation systems in a systematic and centralized way. This paper proposes R.ECOS, a reuse-based ecosystem platform for RS. The proposal evaluation was carried out through a case study. The results point to the solution feasibility, along with the platform components. The main contribution is the implementation of the platform that supports the proposed SECO.