{"title":"使用语言模型和相似度搜索查找flickr资源的位置","authors":"O. Laere, S. Schockaert, B. Dhoedt","doi":"10.1145/1991996.1992044","DOIUrl":null,"url":null,"abstract":"We present a two-step approach to estimate where a given photo or video was taken, using only the tags that a user has assigned to it. In the first step, a language modeling approach is adopted to find the area which most likely contains the geographic location of the resource. In the subsequent second step, a precise location is determined within the area that was found to be most plausible. The main idea of this step is to compare the multimedia object under consideration with resources from the training set, for which the exact coordinates are known, and which were taken in that area. Our final estimation is then determined as a function of the coordinates of the most similar among these resources. Experimental results show this two-step approach to improve substantially over either language models or similarity search alone.","PeriodicalId":390933,"journal":{"name":"Proceedings of the 1st ACM International Conference on Multimedia Retrieval","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"75","resultStr":"{\"title\":\"Finding locations of flickr resources using language models and similarity search\",\"authors\":\"O. Laere, S. Schockaert, B. Dhoedt\",\"doi\":\"10.1145/1991996.1992044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a two-step approach to estimate where a given photo or video was taken, using only the tags that a user has assigned to it. In the first step, a language modeling approach is adopted to find the area which most likely contains the geographic location of the resource. In the subsequent second step, a precise location is determined within the area that was found to be most plausible. The main idea of this step is to compare the multimedia object under consideration with resources from the training set, for which the exact coordinates are known, and which were taken in that area. Our final estimation is then determined as a function of the coordinates of the most similar among these resources. Experimental results show this two-step approach to improve substantially over either language models or similarity search alone.\",\"PeriodicalId\":390933,\"journal\":{\"name\":\"Proceedings of the 1st ACM International Conference on Multimedia Retrieval\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"75\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1st ACM International Conference on Multimedia Retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1991996.1992044\",\"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 of the 1st ACM International Conference on Multimedia Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1991996.1992044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Finding locations of flickr resources using language models and similarity search
We present a two-step approach to estimate where a given photo or video was taken, using only the tags that a user has assigned to it. In the first step, a language modeling approach is adopted to find the area which most likely contains the geographic location of the resource. In the subsequent second step, a precise location is determined within the area that was found to be most plausible. The main idea of this step is to compare the multimedia object under consideration with resources from the training set, for which the exact coordinates are known, and which were taken in that area. Our final estimation is then determined as a function of the coordinates of the most similar among these resources. Experimental results show this two-step approach to improve substantially over either language models or similarity search alone.