{"title":"面向可读性测量的未知文档热图生成","authors":"Jayasankar Santhosh, Shoya Ishimaru, A. Dengel","doi":"10.1145/3379336.3381495","DOIUrl":null,"url":null,"abstract":"The key idea behind this paper is to generate fixation heatmap of unknown documents to visualize and determine the focus areas in a document as a first step towards the readability measurement of the document. The data samples were collected by conducting experiment with nine participants reading 15 documents and the proposed method was to predict the fixation duration of each word in the documents. A Random Forest Regression model was used to predict the fixation duration per word and we achieved a mean regression score (R2) of 0.757 for all the documents.","PeriodicalId":335081,"journal":{"name":"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Generating Heatmap for Unknown Documents towards Readability Measurement\",\"authors\":\"Jayasankar Santhosh, Shoya Ishimaru, A. Dengel\",\"doi\":\"10.1145/3379336.3381495\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The key idea behind this paper is to generate fixation heatmap of unknown documents to visualize and determine the focus areas in a document as a first step towards the readability measurement of the document. The data samples were collected by conducting experiment with nine participants reading 15 documents and the proposed method was to predict the fixation duration of each word in the documents. A Random Forest Regression model was used to predict the fixation duration per word and we achieved a mean regression score (R2) of 0.757 for all the documents.\",\"PeriodicalId\":335081,\"journal\":{\"name\":\"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 25th International Conference on Intelligent User Interfaces Companion\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3379336.3381495\",\"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 25th International Conference on Intelligent User Interfaces Companion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3379336.3381495","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Generating Heatmap for Unknown Documents towards Readability Measurement
The key idea behind this paper is to generate fixation heatmap of unknown documents to visualize and determine the focus areas in a document as a first step towards the readability measurement of the document. The data samples were collected by conducting experiment with nine participants reading 15 documents and the proposed method was to predict the fixation duration of each word in the documents. A Random Forest Regression model was used to predict the fixation duration per word and we achieved a mean regression score (R2) of 0.757 for all the documents.