Chengyang Zhang, Y. Huang, Rada Mihalcea, Hector Cuellar
{"title":"A natural language interface for crime-related spatial queries","authors":"Chengyang Zhang, Y. Huang, Rada Mihalcea, Hector Cuellar","doi":"10.1109/ISI.2009.5137290","DOIUrl":null,"url":null,"abstract":"Web-based mapping applications such as Google Maps or Virtual Earth have become increasingly popular. However, current map search is still keyword-based and supports a limited number of spatial predicates. In this paper, we build towards a natural language query interface to spatial databases to answer crime-related spatial queries. The system has two main advantages compared with interfaces such as Google Maps: (1) It allows query conditions to be expressed in natural language, and (2) It supports a larger number of spatial predicates, such as “within 3 miles” and “close to”. The system is evaluated using a set of crime-related queries run against a dataset that contains many spatial layers in the Denton, Texas area. The results show that our approach significantly outperforms Google Maps when processing complicated spatial queries.","PeriodicalId":210911,"journal":{"name":"2009 IEEE International Conference on Intelligence and Security Informatics","volume":"89 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Intelligence and Security Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISI.2009.5137290","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Web-based mapping applications such as Google Maps or Virtual Earth have become increasingly popular. However, current map search is still keyword-based and supports a limited number of spatial predicates. In this paper, we build towards a natural language query interface to spatial databases to answer crime-related spatial queries. The system has two main advantages compared with interfaces such as Google Maps: (1) It allows query conditions to be expressed in natural language, and (2) It supports a larger number of spatial predicates, such as “within 3 miles” and “close to”. The system is evaluated using a set of crime-related queries run against a dataset that contains many spatial layers in the Denton, Texas area. The results show that our approach significantly outperforms Google Maps when processing complicated spatial queries.