Anika Tabassum, Sukarna Barua, T. Hashem, Tasmin Chowdhury
{"title":"Dynamic Group Trip Planning Queries in Spatial Databases","authors":"Anika Tabassum, Sukarna Barua, T. Hashem, Tasmin Chowdhury","doi":"10.1145/3085504.3085584","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce the concept of \"dynamic groups\" for Group Trip Planning (GTP) queries and propose a novel query type Dynamic Group Trip Planning (DGTP) queries. The traditional GTP query assumes that the group members remain static or fixed during the trip, whereas in the proposed DGTP queries, the group changes dynamically over the duration of a trip where members can leave or join the group at any point of interest (POI) such as a shopping center, a restaurant or a movie theater. The changes of members in a group can be either predetermined (i.e., group changes are known before the trip is planned) or in real-time (changes happen during the trip). In this paper, we provide efficient solutions for processing DGTP queries in the Euclidean space. A comprehensive experimental study using real and synthetic datasets shows that our efficient approach can compute DGTP query solutions within few seconds and significantly outperforms a naive approach in terms of query processing time and I/O access.","PeriodicalId":431308,"journal":{"name":"Proceedings of the 29th International Conference on Scientific and Statistical Database Management","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 29th International Conference on Scientific and Statistical Database Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3085504.3085584","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
In this paper, we introduce the concept of "dynamic groups" for Group Trip Planning (GTP) queries and propose a novel query type Dynamic Group Trip Planning (DGTP) queries. The traditional GTP query assumes that the group members remain static or fixed during the trip, whereas in the proposed DGTP queries, the group changes dynamically over the duration of a trip where members can leave or join the group at any point of interest (POI) such as a shopping center, a restaurant or a movie theater. The changes of members in a group can be either predetermined (i.e., group changes are known before the trip is planned) or in real-time (changes happen during the trip). In this paper, we provide efficient solutions for processing DGTP queries in the Euclidean space. A comprehensive experimental study using real and synthetic datasets shows that our efficient approach can compute DGTP query solutions within few seconds and significantly outperforms a naive approach in terms of query processing time and I/O access.