Jiaxin Mao, Yiqun Liu, N. Kando, Zexue He, Min Zhang, Shaoping Ma
{"title":"A Two-Stage Model for User's Examination Behavior in Mobile Search","authors":"Jiaxin Mao, Yiqun Liu, N. Kando, Zexue He, Min Zhang, Shaoping Ma","doi":"10.1145/3176349.3176891","DOIUrl":null,"url":null,"abstract":"With the rapid growth of mobile search, it is important to understand how users browse the mobile SERPs and allocate their limited attention to each result. To address this problem, we introduce a two-stage examination model that can separately capture the position bias with a skimming model and the attractiveness bias with an attractiveness model. The effectiveness of the proposed model is validated by using a dataset that contains explicit examination feedbacks from users. We further investigate user»s examination behaviors by analyzing the model parameters learned via EM algorithm. The results reveal some interesting findings such as how the skimming behavior is dependent on the previous examination sequence and what factors are associated with the attractiveness of search results on mobile SERPs.","PeriodicalId":198379,"journal":{"name":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2018 Conference on Human Information Interaction & Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3176349.3176891","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
With the rapid growth of mobile search, it is important to understand how users browse the mobile SERPs and allocate their limited attention to each result. To address this problem, we introduce a two-stage examination model that can separately capture the position bias with a skimming model and the attractiveness bias with an attractiveness model. The effectiveness of the proposed model is validated by using a dataset that contains explicit examination feedbacks from users. We further investigate user»s examination behaviors by analyzing the model parameters learned via EM algorithm. The results reveal some interesting findings such as how the skimming behavior is dependent on the previous examination sequence and what factors are associated with the attractiveness of search results on mobile SERPs.