{"title":"VisualizIR:一个在文件中识别和分类相关文本的游戏","authors":"Christopher G. Harris","doi":"10.1145/2399016.2399100","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce VisualizIR, a game where players identify relevant document terms that match predefined categories. VisualizIR evaluates players on accuracy, recall, and precision against an established gold standard, a pooled consensus of judgments made by other players, or a weighted combination of the two. The annotated document can then viewed by any XML-compatible browser, allowing for quick identification of terms in the document related to each category. Here we describe some of the playability design tradeoffs made during the game's development, as well as our findings from two experiments conducted using VisualizIR output.","PeriodicalId":352513,"journal":{"name":"Nordic Conference on Human-Computer Interaction","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"VisualizIR: a game for identifying and categorizing relevant text in documents\",\"authors\":\"Christopher G. Harris\",\"doi\":\"10.1145/2399016.2399100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce VisualizIR, a game where players identify relevant document terms that match predefined categories. VisualizIR evaluates players on accuracy, recall, and precision against an established gold standard, a pooled consensus of judgments made by other players, or a weighted combination of the two. The annotated document can then viewed by any XML-compatible browser, allowing for quick identification of terms in the document related to each category. Here we describe some of the playability design tradeoffs made during the game's development, as well as our findings from two experiments conducted using VisualizIR output.\",\"PeriodicalId\":352513,\"journal\":{\"name\":\"Nordic Conference on Human-Computer Interaction\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nordic Conference on Human-Computer Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2399016.2399100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nordic Conference on Human-Computer Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2399016.2399100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
VisualizIR: a game for identifying and categorizing relevant text in documents
In this paper, we introduce VisualizIR, a game where players identify relevant document terms that match predefined categories. VisualizIR evaluates players on accuracy, recall, and precision against an established gold standard, a pooled consensus of judgments made by other players, or a weighted combination of the two. The annotated document can then viewed by any XML-compatible browser, allowing for quick identification of terms in the document related to each category. Here we describe some of the playability design tradeoffs made during the game's development, as well as our findings from two experiments conducted using VisualizIR output.