How to identify appropriate key-value pairs for querying OSM

Madiha Yousaf, D. Wolter
{"title":"How to identify appropriate key-value pairs for querying OSM","authors":"Madiha Yousaf, D. Wolter","doi":"10.1145/3371140.3371147","DOIUrl":null,"url":null,"abstract":"This paper presents a study on how natural language words that designate types of spatial entities (metropolis, city, creek, etc.) can automatically be translated to the entity classification used in OpenStreetMap (OSM) that assigns key-value tags to entities. The problem of identifying key-value pairs for querying OSM occurs in geographic information retrieval based on natural language text and is difficult for three reasons: Conceptualisation of entities in natural language text and in OSM often differs. Even classification of a single entity type is subject to variations throughout the OSM database. Language is rich and offers many words to communicate nuances of a single entity type. The contribution of this paper is to analyse the contribution of semantic word similarity using Word-Net to identify a mapping from natural language to OSM tags. We present a strategy to identify key-value pairs for natural language words using WordNet and analyse its effectiveness.","PeriodicalId":169676,"journal":{"name":"Proceedings of the 13th Workshop on Geographic Information Retrieval","volume":"C-24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 13th Workshop on Geographic Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3371140.3371147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

This paper presents a study on how natural language words that designate types of spatial entities (metropolis, city, creek, etc.) can automatically be translated to the entity classification used in OpenStreetMap (OSM) that assigns key-value tags to entities. The problem of identifying key-value pairs for querying OSM occurs in geographic information retrieval based on natural language text and is difficult for three reasons: Conceptualisation of entities in natural language text and in OSM often differs. Even classification of a single entity type is subject to variations throughout the OSM database. Language is rich and offers many words to communicate nuances of a single entity type. The contribution of this paper is to analyse the contribution of semantic word similarity using Word-Net to identify a mapping from natural language to OSM tags. We present a strategy to identify key-value pairs for natural language words using WordNet and analyse its effectiveness.
如何为查询OSM识别合适的键值对
本文研究了如何将指定空间实体类型(metropolis, city, creek等)的自然语言单词自动转换为OpenStreetMap (OSM)中使用的实体分类,OSM为实体分配键值标签。识别用于查询OSM的键值对的问题出现在基于自然语言文本的地理信息检索中,困难的原因有三个:自然语言文本和OSM中实体的概念化常常不同。即使是单一实体类型的分类也会受到整个OSM数据库的变化的影响。语言是丰富的,提供了许多词汇来交流单一实体类型的细微差别。本文的贡献在于利用word - net分析语义词相似度对识别自然语言到OSM标签的映射的贡献。提出了一种基于WordNet的自然语言词的键值对识别策略,并对其有效性进行了分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信