Enabling maps/location searches on mobile devices: constructing a POI database via focused crawling and information extraction

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/106700

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106700

Title:	Enabling maps/location searches on mobile devices: constructing a POI database via focused crawling and information extraction
Authors:	張嘉惠;Chuang, Hsiu-Min;Chang, Chia-Hui;Kao, Ting-Yao;Cheng, Chung-Ting;Huang, Ya-Yun;Cheong, Kuo-Pin
Contributors:	資訊電機學院資訊工程學系
Keywords:	geographic information retrieval;Information retrieval;Location based services;Location-based service;POI crawling;POI relation pairing;Smartphones;store name recognition
Date:	2016-07-02
Issue Date:	2026-04-23 13:36:57 (UTC+8)
Publisher:	Taylor and Francis Ltd.;Abingdon: Taylor & Francis
Abstract:	摘要： With the popularity of mobile devices and smartphones, we have witnessed rapid growth in mobile applications and services, especially in location-based services (LBS). According to a mobile marketing survey, maps/location searches are among the most utilized services on smartphones. Points of interest (POIs), such as stores, shops, gas stations, parking lots, and bus stops, are particularly important for maps/location searches. Existing map services such as Google Maps and Wikimapia are constructed manually either professionally or with crowd sourcing. However, manual annotation is costly and limited in current POI search services. With the abundance of information on the Web, many store POIs can be extracted from the Web. In this paper, we focus on automatically constructing a POI database to enable store POI map searches. We propose techniques that are required to construct a POI database, including focused crawling, information extraction, and information retrieval techniques. We first crawl Yellow Page web sites to obtain vocabularies of store names. These vocabularies are then investigated with search engines to obtain sentences containing these store names from search snippets in order to train a store name recognition model. To extract POIs scattered across the Web, we propose a query-based crawler to find address-bearing pages that might be used to extract addresses and store names. We crawled 1.25 million distinct POI pairs scattered across the Web and implemented a POI search service via Apache Lucent's search platform, called Solr. The experimental results demonstrate that the proposed geographical information retrieval model outperforms Wikimapia and a commercial app called 'What's the Number?' 出版者： Abingdon: Taylor & Francis 出版日期： 2016-07-02 出處： International Journal of Geographical Information Science, 2016-07, Vol.30 (7), p.1405-1425 資源來源： Taylor & Francis Journals Auto-Holdings Collection 版權： 2016 Taylor & Francis 2016 版權： 2016 Taylor & Francis 識別號： ISSN: 1365-8816 識別號： EISSN: 1362-3087 識別號： EISSN: 1365-8824 識別號： DOI: 10.1080/13658816.2015.1133820
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	13	View/Open

社群 sharing

Loading...