Shoko Wakamiya, Hiroshi Kawasaki, Yukiko Kawai, A. Jatowt, E. Aramaki, Toyokazu Akiyama
{"title":"Lets not stare at smartphones while walking: memorable route recommendation by detecting effective landmarks","authors":"Shoko Wakamiya, Hiroshi Kawasaki, Yukiko Kawai, A. Jatowt, E. Aramaki, Toyokazu Akiyama","doi":"10.1145/2971648.2971758","DOIUrl":null,"url":null,"abstract":"Navigation in unfamiliar cities often requires frequent map checking, which is troublesome for wayfinders. We propose a novel approach for improving real-world navigation by generating short, memorable and intuitive routes. To do so we detect useful landmarks for effective route navigation. This is done by exploiting not only geographic data but also crowd footprints in Social Network Services (SNS) and Location Based Social Networks (LBSN). Specifically, we detect point, area, and line landmarks by using three indicators to measure landmark's utility: visit popularity, direct visibility, and indirect visibility. We then construct an effective route graph based on the extracted landmarks, which facilitates optimal path search. In the experiments, we show that landmark-based routes out-perform the ones created by baseline from the perspectives of the lap time and the number of references necessary to check self-positions for adjusting route directions.","PeriodicalId":303792,"journal":{"name":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2971648.2971758","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20
Abstract
Navigation in unfamiliar cities often requires frequent map checking, which is troublesome for wayfinders. We propose a novel approach for improving real-world navigation by generating short, memorable and intuitive routes. To do so we detect useful landmarks for effective route navigation. This is done by exploiting not only geographic data but also crowd footprints in Social Network Services (SNS) and Location Based Social Networks (LBSN). Specifically, we detect point, area, and line landmarks by using three indicators to measure landmark's utility: visit popularity, direct visibility, and indirect visibility. We then construct an effective route graph based on the extracted landmarks, which facilitates optimal path search. In the experiments, we show that landmark-based routes out-perform the ones created by baseline from the perspectives of the lap time and the number of references necessary to check self-positions for adjusting route directions.