{"title":"Airbnb研究:视觉描述与产品评级的关系分析","authors":"Chun Kit Fu, Yu Sun","doi":"10.5121/csit.2023.130520","DOIUrl":null,"url":null,"abstract":"Hosts are often desperate to find ways to rent their house, However, most of them do not have possess theknowledge of knowing what type of image cover would grasp the attention of their customer. Gilded by these needs, I have designed an application that uses machine learning to find the relationship between the images andtheirrating [1]. I first used JSON to convert the HTML file resource to a format where we can use in python for webscraping [2]. This paper designs an application tool to find all the object or characters inside images by webscraping and changes it into a model for machine learning [3]. Applied our application to predict the ratingandconducted a qualitative evaluation of the approach. In order to prove our result, I imported an image fromAirbnband found its rating. It turns out that the predicted rating is extremely close to the real rating, Proving The system’susability.","PeriodicalId":261978,"journal":{"name":"Computer Science, Engineering and Applications","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Airbnb Research: An Analysis in Nexus BetweenVisual Description and Product Rating\",\"authors\":\"Chun Kit Fu, Yu Sun\",\"doi\":\"10.5121/csit.2023.130520\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hosts are often desperate to find ways to rent their house, However, most of them do not have possess theknowledge of knowing what type of image cover would grasp the attention of their customer. Gilded by these needs, I have designed an application that uses machine learning to find the relationship between the images andtheirrating [1]. I first used JSON to convert the HTML file resource to a format where we can use in python for webscraping [2]. This paper designs an application tool to find all the object or characters inside images by webscraping and changes it into a model for machine learning [3]. Applied our application to predict the ratingandconducted a qualitative evaluation of the approach. In order to prove our result, I imported an image fromAirbnband found its rating. It turns out that the predicted rating is extremely close to the real rating, Proving The system’susability.\",\"PeriodicalId\":261978,\"journal\":{\"name\":\"Computer Science, Engineering and Applications\",\"volume\":\"93 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Science, Engineering and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/csit.2023.130520\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Science, Engineering and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/csit.2023.130520","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Airbnb Research: An Analysis in Nexus BetweenVisual Description and Product Rating
Hosts are often desperate to find ways to rent their house, However, most of them do not have possess theknowledge of knowing what type of image cover would grasp the attention of their customer. Gilded by these needs, I have designed an application that uses machine learning to find the relationship between the images andtheirrating [1]. I first used JSON to convert the HTML file resource to a format where we can use in python for webscraping [2]. This paper designs an application tool to find all the object or characters inside images by webscraping and changes it into a model for machine learning [3]. Applied our application to predict the ratingandconducted a qualitative evaluation of the approach. In order to prove our result, I imported an image fromAirbnband found its rating. It turns out that the predicted rating is extremely close to the real rating, Proving The system’susability.