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基于GeoNames和Solr的地名数据全文检索 被引量:3
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作者 魏勇 胡丹露 +1 位作者 李响 王丰 《测绘工程》 CSCD 2016年第2期28-32,共5页
地名数据是一种重要的地理信息资源,目前我国的地名数据库建设多局限于国内地名,缺少国外数据。传统地名数据的检索多为关键字查询,查询效率低且无法用于复杂地名查询。文中提出一种基于开源地名数据库GeoNames和开源搜索引擎Solr的地... 地名数据是一种重要的地理信息资源,目前我国的地名数据库建设多局限于国内地名,缺少国外数据。传统地名数据的检索多为关键字查询,查询效率低且无法用于复杂地名查询。文中提出一种基于开源地名数据库GeoNames和开源搜索引擎Solr的地名数据全文检索方法,通过分析GeoNames的数据类型和结构,构建MySQL地名数据库,并利用Solr建立地名索引,提供基于Web服务的地名数据全文检索。实验表明,基于Solr的地名数据全文检索能够显著提高地名数据检索效率,对于复杂地名查询,也能进行有效地检索。 展开更多
关键词 地名数据 geonames SOLR 全文检索 WEB服务
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Geographic variability of Twitter usage characteristics during disaster events 被引量:3
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作者 Kiran Zahra Frank O.Ostermann Ross S.Purves 《Geo-Spatial Information Science》 SCIE EI CSCD 2017年第3期231-240,共10页
Twitter is a well-known microblogging platform for rapid diffusion of views,ideas,and information.During disasters,it has widely been used to communicate evacuation plans,distribute calls for help,and assist in damage... Twitter is a well-known microblogging platform for rapid diffusion of views,ideas,and information.During disasters,it has widely been used to communicate evacuation plans,distribute calls for help,and assist in damage assessment.The reliability of such information is very important for decision-making in a crisis situation,but also difficult to assess.There is little research so far on the transferability of quality assessment methods from one geographic region to another.The main contribution of this research is to study Twitter usage characteristics of users based in different geographic locations during disasters.We examine tweeting activity during two earthquakes in Italy and Myanmar.We compare the granularity of geographic references used,user profile characteristics that are related to credibility,and the performance of Naive Bayes models for classifying Tweets when used on data from a different region than the one used to train the model.Our results show similar geographic granularity for Myanmar and Italy earthquake events,but the Myanmar earthquake event has less information from locations nearby when compared to Italy.Additionally,there are significant and complex differences in user and usage characteristics,but a high performance for the Naive Bayes classifier even when applied to data from a different geographic region.This research provides a basis for further research in credibility assessment of users reporting about disasters. 展开更多
关键词 Geographic feature granularity Volunteered Geographic Information(VGI) Naive Bayes TWITTER CREDIBILITY geonames
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