• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.81-89
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• 2019

As the need for the integration of administrative datasets and address information increases, there is also growing interest in POI (Point of Interest) data as a source of location information across applications and platforms. The purpose of this study is to develop an alias database management method for efficient POI searching, based on POI data representing position. First, we determine the attributes of POI alias data as it is used variously by individual users. When classifying aliases of POIs, we excluded POIs in which the typo and names are all in English alphabet. The attributes of POI aliases are classified into four categories, and each category is reclassified into three classes according to the strength of the attributes. We then define the quality of POI aliases classified in this study through experiments. Based on the four attributes of POI defined in this study, we developed a method of managing one POI alias through and integrated method composed of word embedding and a similarity measurement. Experimental results of the proposed POI alias management method show that it is possible to utilize the algorithm developed in this study if there are small numbers of aliases in each POI with appropriate POI attributes defined in this study.

• Journal of Digital Contents Society
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• v.14 no.4
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• pp.463-469
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• 2013

The set-based POI search algorithm showed better performance than the existing hard matching search when inaccurate queries are entered. In the set-based POI search algorithm, however, there is a problem that can't classify duplicate characters within a record. This is due to it's 'set-based' search property. To solve this problem, we improve the existing set-based POI search algorithm. In this paper, we propose and implement an improved set-based POI search algorithm that is able to deal duplicate characters properly. From the experimental results, we can find that our technique for duplicate characters improves the performance of the existing set based POI search algorithm.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.256-259
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• 2004

Recently, Location-based services(LBS) allow consumers to receive services based on their geographic location data. Users want to take services based location information with portable devices. And Point of Interest(POI) information's usage is increasing with mobile device's development and user's interest. And this paper shows that we connect the multimedia POI database(DB), provide the multimedia services through the portable devices and search POI using location and direction information. The multimedia POI is consisted of sound, image, moving image and animation with location information. When we search POI, we find POI in DB using the area zone and direction information.[l]

• Journal of KIISE:Software and Applications
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• v.36 no.3
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• pp.226-235
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• 2009

People use various information for searching POI in the navigation system such as name, category, address, phone number. Most of users use name and category to search their POT. They don't know exact name in POI DB provided by Maker. They use abbreviated or generalized name as key word for searching POI. Because of these reasons, the hit ratio has been very low. In this paper, We suggest a extra DB_construction system for raising the hit ratio. It generates allomorphes DB link to the POI name in original DB. We classified the POI names in original DB into seven types of allomorph by analyzing the gathered patterns from the POI DB which has over 650,000 entries. For auto_generating the allomorphes, we made 577 rules based on the classified types. And we generated the allomorphes manually for the entries which are difficult to make the rule and has low frequency The generated allomorphes account for 35.8% of all original DB. The hit ratio is 89% under suggested system.

• Spatial Information Research
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• v.22 no.4
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• pp.21-38
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• 2014

Since users who search maps conduct their searching using the name they already know or is commonly called rather than formal name of a specific place, they tend to fail to find their destination. In addition, in typical web map service in terms of spatial searching of map. Location information of unintended place can be provided because when spatial searching is conducted with the vocabulary 'nearby' and 'in the vicinity', location exceeding 2 km from the current location is searched altogether as well. In this research, spatial range that human can perceive is calculated by extracting POI date with the usage of twitter data of SNS, constructing spatial relations with existing POI, which is already constructed. As a result, various place names acquired could be utilized as different names of existing POI data and it is expected that new POI data would contribute to select places for constructing POI data by utilizing to recognize places having lots of POI variation. Besides, we also expect efficient spatial searching be conducted using diverse spatial vocabulary which can be used in spatial searching and spatial range that human can perceive.

• Spatial Information Research
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• v.20 no.3
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• pp.67-81
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• 2012

Due to the recent advancement of cloud computing, the research on database outsourcing has been actively done. Moreover, the number of users who utilize Location-based Services(LBS) has been increasing with the development in w ireless communication technology and mobile devices. Therefore, LBS providers attempt to outsource their spatial database to service provider, in order to reduce costs for data storage and management. However, because unauthorized access to sensitive data is possible in spatial database outsourcing, it is necessary to study on the preservation of a user's privacy. Thus, we, in this paper, propose a spatial data encryption scheme to produce outsourced database from an original database. We also propose a k-Nearest Neighbor(k-NN) query processing algorithm that efficiently performs k-NN by using the outsourced database. Finally, we show from performance analysis that our algorithm outperforms the existing one.

• Database Research
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• v.34 no.3
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• pp.86-98
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• 2018

Point-of-Interest(POI) recommendation systems suggest the most interesting POIs to users considering the current location and time. With the rapid development of smartphones, internet-of-things, and location-based social networks, it has become feasible to accumulate huge amounts of user POI visits. Therefore, instant recommendation of interesting POIs at a given time is being widely recognized as important. To increase the performance of POI recommendation systems, several studies extracting users' POI sequential preference from POI check-in data, which is intended for implicit feedback, have been suggested. However, when constructing a model utilizing sequential preference, the model encounters possibility of data distortion because of a low number of observed check-ins which is attributed to intensified data sparsity. This paper suggests refinement of temporal intervals based on data confidence. When building a POI recommendation system using temporal intervals to model the POI sequential preference of users, our methodology reduces potential data distortion in the dataset and thus increases the performance of the recommendation system. We verify our model's effectiveness through the evaluation with the Foursquare and Gowalla dataset.

• Journal of Korea Spatial Information System Society
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• v.9 no.3
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• pp.67-80
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• 2007

Recently, many studies on query processing algorithms has been done for spatial networks, such as roads and railways, instead of Euclidean spaces, in order to efficiently support LBS(location-based service) and Telematics applications. However, both a closest pairs query and an e-distance join query require a very high cost in query processing because they can be answered by processing a set of POIs, instead of a single POI. Nevertheless, the query processing cost for closest pairs and e-distance join queries is rapidly increased as the number of k (or the length of radius) is increased. Therefore, we propose both a closest pairs query processing algorithm and an e-distance join query processing algorithm using a POI-based materialization technique so that we can process closest pairs and e-distance join queries in an efficient way. In addition, we show the retrieval efficiency of the proposed algorithms by making a performance comparison of the conventional algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.208-210
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• 2008

정형 정보를 저장하는 대표적인 수단인 Microsoft Excel과 Database 간 상호변환에 있어서 다양한 방법들 중 Web을 기반으로 하는 변환 기술은 활용도가 매우 높을 것이다. 특히 많은 자료가 엑셀로 관리되는 경우 데이터 중복의 문제가 발생하며 DB를 통한 통합관리는 사용자 편의성 측면에서 높은 필요성을 갖는다. 본 논문은 이런 문제를 해결하기 위한 방안으로 POI를 이용한 변환 기법을 소개한다.

• Spatial Information Research
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• v.21 no.1
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• pp.1-13
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• 2013

This paper describes a GIS framework for geo-semantic information retrieval in mobile computing environments. We built geographic ontologies of POI (point of interest) and weather information for use in the combination of semantic, spatial, and temporal functions in a fully integrated database. We also implemented a geo-semantic app for Android-based smartphones that can extract more appropriate POIs in terms of user contexts and geographic ontologies and can visualize the POIs using Google Maps API (application programming interface). The feasibility tests showed our geo-semantic app can provide pertinent POI information according to mobile user contexts such as location, time, schedule, and weather. We can discover a baking CVS (convenience store) in the test of bakery search and can find out a drive-in theater for a not rainy day, which are good examples of the geo-semantic query using semantic, spatial, and temporal functions. As future work, we should need ontology-based inference systems and the LOD (linked open data) of various ontologies for more advanced sharing of geographic knowledge.