• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.3
• /
• pp.176-184
• /
• 2023

Points of interest (POIs) are widely used in tourism recommendations and to provide information about areas of interest. Currently, situation judgement using POI and GPS data is mainly rule-based. However, this approach has the limitation that inferences can only be made using predefined POI information. In this study, we propose an algorithm that uses POI data, GPS data, and schedule information to calculate the current speed, location, schedule matching, movement trajectory, and POI coverage, and uses machine learning to determine whether to stay or go. Based on the input data, the clustered information is labelled by k-means algorithm as unsupervised learning. This result is trained as the input vector of the SVM model to calculate the probability of moving and staying. Therefore, in this study, we implemented an algorithm that can adjust the schedule using the travel schedule, POI data, and GPS information. The results show that the algorithm does not rely on predefined information, but can make judgements using GPS data and POI data in real time, which is more flexible and reliable than traditional rule-based approaches. Therefore, this study can optimize tourism scheduling. Therefore, the stay detection algorithm using GPS movement trajectories and POIs developed in this study provides important information for tourism schedule planning and is expected to provide much value for tourism services.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.15 no.3
• /
• pp.43-50
• /
• 2015

Google, Yahoo, Daum and Naver has the POI(point of interest) service. And POI on the map is expending to social commerce, SNS, social game and social shopping. At the same time the uses's position on the map is the starting point of the Humanities Story. That means our current position is the place for stories of tales, children's song, fictional characters, the film background, lyrics and the birth of great people. This study points out that service has the limited to cafe, restaurant and hospital, and suggests the Humanities fusion Map Service which is combined with the POI information.

• Journal of Information Technology Services
• /
• v.10 no.4
• /
• pp.269-280
• /
• 2011

Mobile Augmented Reality (mobile AR), as one of the most prospective mobile applications, intends to provide richer experiences by annotating tags or virtual objects over the scene observed through camera embedded in a handheld device like smartphone or pad. In this paper, we analyzed the current status of the art of mobile AR and proposed a novel Points of Interest (POIs) data model based on ontology to provide context-aware information retrievals on lots of POIs data. Proposed ontology was expanded from the standard POIs data model of W3C POIs Working Group and established using OWL (Web Ontology Language) and Protege. We also proposed a context-aware mobile AR platform which can resolve three distinguished issues in current platforms : interoperability problem of POI tags, POIs data retrieval issue, and context-aware service issue.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.1
• /
• pp.205-211
• /
• 2012

In this paper, we proposed a context-aware augmented reality platform for mobile augmented reality to support user-oriented virtual world information for smartphone user. We designed the platform architecture and 6 subsystems which are derived from the analysis of existing augmented reality applications and platforms. The proposed architecture includes a context reasoning service subsystem for the context-aware information filtering, and separates the inner platform from the outer virtual world network containing virtual information to resolve interoperability issue of POI(Points of Interest) data.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.10
• /
• pp.439-446
• /
• 2015

Recently, semantic trajectories which combine GPS positions and POIs(Point of Interests) become more popular in order to expand location based services. To construct semantic trajectories, the existing algorithms exploit the extent information of POIs described as polygons and find overlapping regions between GPS positions and the extents. However, the algorithms are not applicable in the condition where the extent information is not provided such as in Google Map, Naver Map, OpenStreetMap and most of the open geographic information systems. In this paper, we provide a novel algorithm to construct semantic trajectories only with GPS positions and POI points but without POI extents.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.5
• /
• pp.359-366
• /
• 2019

Indoor spatial data has great importance as the demand for representing the complex urban environment in the context of providing LBS (Location-based Services) is increasing. IndoorGML (Indoor Geographic Markup Language) has been established as the data standard for spatial data in providing indoor navigation, but its definitions and relationships must be expanded to increase its applications and to successfully delivering information to users. In this study, we propose an approach to integrate IndoorGML with Indoor POI (Points of Interest) data by extending the IndoorGML notion of space and topological relationships. We consider two cases of representing Indoor POI, by 3D geometry and by point primitive representation. Using the concepts of the NRS (node-relation structure) and multi-layered space representation of IndoorGML, we define layers to separate features that represent the spaces and the Indoor POI into separate, but related layers. The proposed methodology was implemented with real datasets to evaluate its effectiveness for performing indoor spatial analysis.

• KIISE Transactions on Computing Practices
• /
• v.20 no.12
• /
• pp.652-657
• /
• 2014

Given a starting point, destination point and various Points Of Interest (POIs), which contain a full or partial order, for a user to visit we wish to create, a sequenced route from the starting point to the destination point that includes one member of each POI type in a particular order. This paper proposes a method for finding the approximate shortest route between the start point, destination point and one member of each POI type. There are currently two algorithms that perform this task but they both have weaknesses. One of the algorithms only considers the distance between the visited POI (or starting point) and POI to visit next. The other algorithm chooses candidate points near the straight-line distance between the start point and destination but does not consider the order of visits on the corresponding network path. This paper outlines an algorithm that chooses the candidate points that are nearer to the network path between the start point and destination using network search. The algorithm looks for routes using the candidate points and finds the approximate shortest route by assigning an adaptive priority to the route that visits more POIs in a short amount of time.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.5
• /
• pp.81-91
• /
• 2012

Recently, as location-determination of indoor users is available with the development of variety of localization techniques for indoor location-based service, diverse indoor location based services are proposed. Accordingly, it is necessary to develop individualized POI recommendation service for recommending most interested points of large-scale commercial spaces such as shopping malls and departments. For POI recommendation, it is necessary to study the method for exploring location which users are interested in location with considering user's mobility in large-scale commercial spaces. In this paper, we proposed POI recommendation system with the definition of users' as 'Stay point' in order to consider users' various interest locations. By using the proposed algorithm, we analysis users' Stay points, then mining the users' visiting pattern to finished the proposed. POI Recommendation System. The proposed system decreased data more dramatically than that of using user's entire mobility data and usage of memory.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.5
• /
• pp.467-476
• /
• 2020

Indoor space has been one of the focal points for geospatial research as various factors such as increasing demands for application and demand for adaptive response in emergencies have arisen. IndoorGML (Indoor Geography Markup Language) has provided a standardized method of representing the topological aspect of micro-scale environments, with its extensive specifications and flexible applicability. However, as more real-world problems and needs demand attention, suggestions to improve this standard, such as representing IndoorPOI (Indoor Points of Interest), have arisen. Hence, existing algorithms and functionalities that we use on perceiving these indoor spaces must also adapt to accommodate said improvements. In this study, we explore how to define spatial neighborhoods in indoor spaces represented by an integrated IndoorGML and IndoorPOI data. We revisit existing approaches to combine the aforementioned datasets and refine previous approaches to perform neighborhood spatial queries in 3D. We implement the proposed algorithm in three use cases using sample datasets representing a real-world structure to demonstrate its effectiveness for performing indoor spatial analysis.

• Journal of Korea Spatial Information System Society
• /
• v.9 no.3
• /
• pp.51-65
• /
• 2007

In order to analyze moving object trajectories on road networks, its representation needs to be defined correctly. The most previous methods representing moving object trajectories on road networks defined moving object trajectories as a set of passed location and its time. It is required much time in processing analysis such as retrieval for moving object trajectories. In this paper, we focus on POI(Points of Interest) on road networks and propose methods simplifying moving object trajectories based on it. Our method simplifies moving object trajectories by reducing the number of POIs that moving object trajectories passed and maintains its form after moving object trajectories were simplified.