{"title":"音乐数据的数字索引","authors":"Yu-lung Lo, Shiou-jiuan Chen","doi":"10.1109/ICDCSW.2002.1030779","DOIUrl":null,"url":null,"abstract":"The management of large collections of music data in a multimedia database has received much attention in the past few years. In most current work, researchers extract features from the music data and develop indices that will help to retrieve the relevant music quickly. Several reports have pointed out that these features of music can be transformed and represented in the form of music feature strings. However, these approaches lack scalability upon increasing music data. In this paper we propose an approach to transform music data into numeric forms and develop an index structure base on the R-tree for effective retrieval. The experimental results show that our approach outperforms existing string index approaches.","PeriodicalId":382808,"journal":{"name":"Proceedings 22nd International Conference on Distributed Computing Systems Workshops","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"The numeric indexing for music data\",\"authors\":\"Yu-lung Lo, Shiou-jiuan Chen\",\"doi\":\"10.1109/ICDCSW.2002.1030779\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The management of large collections of music data in a multimedia database has received much attention in the past few years. In most current work, researchers extract features from the music data and develop indices that will help to retrieve the relevant music quickly. Several reports have pointed out that these features of music can be transformed and represented in the form of music feature strings. However, these approaches lack scalability upon increasing music data. In this paper we propose an approach to transform music data into numeric forms and develop an index structure base on the R-tree for effective retrieval. The experimental results show that our approach outperforms existing string index approaches.\",\"PeriodicalId\":382808,\"journal\":{\"name\":\"Proceedings 22nd International Conference on Distributed Computing Systems Workshops\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 22nd International Conference on Distributed Computing Systems Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDCSW.2002.1030779\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 22nd International Conference on Distributed Computing Systems Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCSW.2002.1030779","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The management of large collections of music data in a multimedia database has received much attention in the past few years. In most current work, researchers extract features from the music data and develop indices that will help to retrieve the relevant music quickly. Several reports have pointed out that these features of music can be transformed and represented in the form of music feature strings. However, these approaches lack scalability upon increasing music data. In this paper we propose an approach to transform music data into numeric forms and develop an index structure base on the R-tree for effective retrieval. The experimental results show that our approach outperforms existing string index approaches.