Cátia Moreira, João Taborda, R. Gaudio, Lara dos Santos, Paulo Pereira
{"title":"Contextualizing Data on a Content Management System","authors":"Cátia Moreira, João Taborda, R. Gaudio, Lara dos Santos, Paulo Pereira","doi":"10.1145/2810133.2810134","DOIUrl":null,"url":null,"abstract":"Content Management Systems (CMSs) are known for their ability for storing data, both structured and non-structured data. However they are not able to associate meaning and context to the stored information. Furthermore, these systems do not meet the needs and expectations of their users, because as the size of data increases, the system loses its capacity of retrieving meaningful results. In order to overcome this issue, we propose a method to implement data contextualization on a CMS. The proposed method consists of enriching the data with semantic information, allowing a more accurate retrieval of results. The implementation of this approach was validated by applying this contextualization method to a currently used CMS with real information. With this improved CMS, it is expected that the users will be able to retrieve data related to their initial search.","PeriodicalId":298747,"journal":{"name":"Proceedings of the Eighth Workshop on Exploiting Semantic Annotations in Information Retrieval","volume":"483 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Eighth Workshop on Exploiting Semantic Annotations in Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2810133.2810134","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Content Management Systems (CMSs) are known for their ability for storing data, both structured and non-structured data. However they are not able to associate meaning and context to the stored information. Furthermore, these systems do not meet the needs and expectations of their users, because as the size of data increases, the system loses its capacity of retrieving meaningful results. In order to overcome this issue, we propose a method to implement data contextualization on a CMS. The proposed method consists of enriching the data with semantic information, allowing a more accurate retrieval of results. The implementation of this approach was validated by applying this contextualization method to a currently used CMS with real information. With this improved CMS, it is expected that the users will be able to retrieve data related to their initial search.