{"title":"RecSys for distributed events: investigating the influence of recommendations on visitor plans","authors":"Richard Schaller, Morgan Harvey, David Elsweiler","doi":"10.1145/2484028.2484119","DOIUrl":null,"url":null,"abstract":"Distributed events are collections of events taking place within a small area over the same time period and relating to a single topic. There are often a large number of events on offer and the times in which they can be visited are heavily constrained, therefore the task of choosing events to visit and in which order can be very difficult. In this work we investigate how visitors can be assisted by means of a recommender system via 2 large-scale naturalistic studies (n=860 and n=1047). We show that a recommender system can influence users to select events that result in tighter and more compact routes, thus allowing users to spend less time travelling and more time visiting events.","PeriodicalId":178818,"journal":{"name":"Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval","volume":"XCV 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2484028.2484119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17
Abstract
Distributed events are collections of events taking place within a small area over the same time period and relating to a single topic. There are often a large number of events on offer and the times in which they can be visited are heavily constrained, therefore the task of choosing events to visit and in which order can be very difficult. In this work we investigate how visitors can be assisted by means of a recommender system via 2 large-scale naturalistic studies (n=860 and n=1047). We show that a recommender system can influence users to select events that result in tighter and more compact routes, thus allowing users to spend less time travelling and more time visiting events.