Store Name Extraction and Name-Address Matching for Geographic Information Retrieval

• Main Authors: Yu-Yang Lin, 林育暘
• Other Authors: Chia-Hui Chang
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/11588483903176116990

碩士 === 國立中央大學 === 資訊工程學系 === 102 === Mobile devices are the trend of 2014. According to the report of IDC, the first time unit shipments of tablet has exceed PCs in 2013 Q4. The smart phone has already exceed other devices in unit shipments and market ratio. LBS (Location-based Service) plays an important role in this trend. Because of the device mobility, many demand have been proposed, for example, navigation, searching restaurant or gas station. It’s usually needs a POI (Point-of Interest) database to support a LBS. The web is the largest data source, these data come from website manager, crowdsourcing and people sharing information, including address, name, phone and comment. There are many method to extract address associated information nowadays, but they are usually faced with the challenge of extracting name of POI. It’s a limitation of information retrieval. Our system could be separated into three parts: the Taiwan address normalization, the Store Name Entity Recognition and Address-StoreNE matching. Finally, users can search the store names on the mobile device and get the informations like address, telephone and comment immediately. In the part of Store NER, our research propose a common characteristic of store and organization names. We use these characteristic as features to join the CRF model, enhanced the recognition result.