{"title":"根据用户生成的内容为GIR评估创建测试集合","authors":"Damien Palacio, C. Derungs, R. Purves","doi":"10.1145/2533888.2533934","DOIUrl":null,"url":null,"abstract":"Evaluation of the effectiveness of Geographic Information Retrieval (GIR) systems is challenging and time consuming. We describe an approach to such evaluations, where we use user generated content in the form of text and associated metadata to build a large test colletion automatically. We can thus show that the UGC test collection is useful for evaluating and exploring some of the critical aspects of a GIR, for instance by submitting large numbers of queries.","PeriodicalId":167948,"journal":{"name":"Workshop on Geographic Information Retrieval","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Creating test collections from user generated content for GIR evaluation\",\"authors\":\"Damien Palacio, C. Derungs, R. Purves\",\"doi\":\"10.1145/2533888.2533934\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Evaluation of the effectiveness of Geographic Information Retrieval (GIR) systems is challenging and time consuming. We describe an approach to such evaluations, where we use user generated content in the form of text and associated metadata to build a large test colletion automatically. We can thus show that the UGC test collection is useful for evaluating and exploring some of the critical aspects of a GIR, for instance by submitting large numbers of queries.\",\"PeriodicalId\":167948,\"journal\":{\"name\":\"Workshop on Geographic Information Retrieval\",\"volume\":\"101 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop on Geographic Information Retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2533888.2533934\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Geographic Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2533888.2533934","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Creating test collections from user generated content for GIR evaluation
Evaluation of the effectiveness of Geographic Information Retrieval (GIR) systems is challenging and time consuming. We describe an approach to such evaluations, where we use user generated content in the form of text and associated metadata to build a large test colletion automatically. We can thus show that the UGC test collection is useful for evaluating and exploring some of the critical aspects of a GIR, for instance by submitting large numbers of queries.