{"title":"有效的图像重新排序利用点击数据","authors":"Shusheng Cen, Lezi Wang, Yanchao Feng, Hongliang Bai, Yuan Dong","doi":"10.1109/ICMEW.2014.6890605","DOIUrl":null,"url":null,"abstract":"This paper introduces our system competing in MSR-Bing Image Retrieval Challenge at ICME 2014. The task of the challenge is to rank images by their relevance to a given topic, by leveraging cues hidden in search engine's click log. With the successful trial in last year's challenge, search-based method is shown to be effective in this task. We reserve the basic idea of search-based method in our new system, and there are also some improvements made this time. The first one is an adjustment in textual search algorithm for related clicked images in database. We simplified the previous scheme and make it more straight-forward and effient. The second inovation is using support vector machines to predict the relevance of query-image pair.","PeriodicalId":178700,"journal":{"name":"2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Efficient image reranking by leveraging click data\",\"authors\":\"Shusheng Cen, Lezi Wang, Yanchao Feng, Hongliang Bai, Yuan Dong\",\"doi\":\"10.1109/ICMEW.2014.6890605\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces our system competing in MSR-Bing Image Retrieval Challenge at ICME 2014. The task of the challenge is to rank images by their relevance to a given topic, by leveraging cues hidden in search engine's click log. With the successful trial in last year's challenge, search-based method is shown to be effective in this task. We reserve the basic idea of search-based method in our new system, and there are also some improvements made this time. The first one is an adjustment in textual search algorithm for related clicked images in database. We simplified the previous scheme and make it more straight-forward and effient. The second inovation is using support vector machines to predict the relevance of query-image pair.\",\"PeriodicalId\":178700,\"journal\":{\"name\":\"2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-07-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMEW.2014.6890605\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMEW.2014.6890605","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient image reranking by leveraging click data
This paper introduces our system competing in MSR-Bing Image Retrieval Challenge at ICME 2014. The task of the challenge is to rank images by their relevance to a given topic, by leveraging cues hidden in search engine's click log. With the successful trial in last year's challenge, search-based method is shown to be effective in this task. We reserve the basic idea of search-based method in our new system, and there are also some improvements made this time. The first one is an adjustment in textual search algorithm for related clicked images in database. We simplified the previous scheme and make it more straight-forward and effient. The second inovation is using support vector machines to predict the relevance of query-image pair.