• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.860-879
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• 2002

Traditionally, Geographical Information Systems can only process spatial data in a procedure-oriented way, and the data can't be treated integrally. This method limits the development of spatial data applications. A new and promising method to solve this problem is the spatial structural query language, which extends SQL and provides integrated accessing to spatial data. In this paper, the theory of spatial structural query language is discussed, and a new geographical data model based on the concepts and data model in OGIS is introduced. According to this model, we implemented a spatial structural query language G/SQL. Through the studies of the 9-Intersection Model, G/SQL provides a set of topological relational predicates and spatial functions for GIS application development. We have successfully developed a Web-based GIS system-WebGIS-using G/SQL. Experiences show that the spatial operators G/SQL offered are complete and easy-to-use. The BNF representation of G/SQL syntax is included in this paper.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1259-1276
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• 2017

As technologies related to sensor network are currently emerging and the use of GeoSensor is increasing along with the development of Internet of Things (IoT) technology, spatial query processing systems to efficiently process spatial sensor data are being actively studied. However, existing spatial query processing systems do not support a spatial-temporal data type and a spatial-temporal operator for processing spatialtemporal sensor data. Therefore, they are inadequate for processing spatial-temporal sensor data like GeoSensor. Accordingly, this paper developed a spatial-temporal query processing system, for efficient spatial-temporal query processing of spatial-temporal sensor data in a sensor network. Lastly, this paper verified the utility of System through a scenario, and proved that this system's performance is better than existing systems through performance assessment of performance time and memory usage.

• Journal of Information Processing Systems
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• v.5 no.4
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• pp.229-236
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• 2009

Sensors are deployed to gather physical, environmental data in sensor networks. Depending on scenarios, it is often assumed that it is difficult for batteries to be recharged or exchanged in sensors. Thus, sensors should be able to process users' queries in an energy-efficient manner. This paper proposes a spatial query processing scheme- Minimum Bounding Area Based Scheme. This scheme has a purpose to decrease the number of outgoing messages during query processing. To do that, each sensor has to maintain some partial information locally about the locations of descendent nodes. In the initial setup phase, the routing path is established. Each child node delivers to its parent node the location information including itself and all of its descendent nodes. A parent node has to maintain several minimum bounding boxes per child node. This scheme can reduce unnecessary message propagations for query processing. Finally, the experimental results show the effectiveness of the proposed scheme.

• KIISE Transactions on Computing Practices
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• v.21 no.7
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• pp.452-457
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• 2015

In this paper, we propose a spatial query processor, SQUERY, which can derive rich query results through spatial reasoning on the initial knowledge base, as well as, process both qualitative and quantitative queries about the topological and directional relationships between spatial objects. In order to derive richer query results, the query processor expands the knowledge base by applying forward spatial reasoning into the initial knowledge base in a preprocessing step. The proposed query processor uses not only qualitative spatial knowledge describing topological/directional relationship between spatial objects, but also utilizes quantitative spatial knowledge including geometric data of individual spatial objects through geometric computation. The results of an experiment with the OSM(Open Street Map) spatial knowledge base demonstrates the high performance of our spatial query processing system.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.286-295
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• 2003

The shape of query windows for spatial selection queries is a rectangle in many cases. However, it can be issued for spatial selection queries with not only rectangular query widow, but also polygonal query window. Moreover, as the applications like GIS can manage much more spatial data, they can support the more various applications. Therefore it is valuable for considering about the query processing method suitable for not only rectangle query window, but also general polygonal one. It is the general state-of-the-art approach to use the plane- sweep technique as the computation algorithm in the refinement step as the spatial join queries do. However, from the observation on the characteristics of spatial data and query windows, we can find in many cases that the shape of query window is much simpler than that of spatial data. From these observations, we suggest a new refinement process approach which is suitable for this situation. Our experiments show that, if the number of vertices composing the query window is less than about 20, the new approach we suggest is superior to the state-of-the-art approach by about 20% in general cases.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.79-86
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• 2009

The tuple of constraint database consists of constraint logical formula and it could process the presentation and query of the constraint database simply. Query operation processing shall include the constraint formula between related tuple such as selection, union, intersection of spatial data through the constraint database. However, this could produce the increasing of duplicated or unnecessary data. Hence, it will drive up the cost as per quality. This paper identified problems regarding query processing result in the constraint database. Also this paper suggested the tuple minimization summary method for result relation and analyzed the effects for efficient query processing. We were able to identify that the effectiveness of the query processing was enhanced by eliminating unnecessary constraint formula of constraint relation using the tuple minimization method.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.551-562
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• 2000

Content-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. GContent-based image retrieval system retrieves an image from a database using visual features. Among approaches to express visual aspects in queries, 'query by sketch' is most convenient and expressive. However, every 'query by sketch' system has the query imperfectness problem. Generally, the query image produced by a user is different from the intended target image. To overcome this problem, many image retrieval systems use the spatial relationships of the objects, instead of pixel coordinates of the objects. In this paper, a query-converting algorithm for an image retrieval system, which uses the spatial relationship of every two objects as an image feature, is proposed. The proposed algorithm converts the query image into a graph that has the minimum number of edges, by eliminating every transitive edge. Since each edge in the graph represents the spatial relationship of two objects, the elimination of unnecessary edges makes the retrieval process more efficient. Experimental results show that the proposed algorithm leads the smaller number of comparison in searching process as compared with other algorithms that do not guarantee the minimum number of edges.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1166-1176
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• 1999

The spationtemporal databases support a historical informations as well as spatial managements for various kinds of objects in the real world, and can be efficiently used in many applications such as geographic information system, urban plan system, car navigation system. However it is difficult to represent efficiently historical operations with conventional database query language for spatial objects. In terms of cost for query processing, it also degenerates performance of query processing because of syntactic limitations which is innate in conventional query representation. So in this paper, we introduce a new query language, entitled as STQL, which has been extended on the basis of the most popular relational database query language SQL. And we implement as well as evaluate a spationtemporal query processing system that get a query written by STQL and then process it in a main memory.

• 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.

• Spatial Information Research
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• v.21 no.2
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• pp.23-33
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• 2013

W ith the recent advancement of IoT (Internet of Things) technology, there has been much interest in the spatial query processing which energy-efficiently acquires sensor readings from sensor nodes inside specified geographical area of interests. Therefore, various kinds of spatial query processing algorithms and distributed spatial indexing methods have been proposed. They can minimize energy consumption of sensor nodes by reducing wireless communication among them using in-network spatial filtering technology. However, they cannot optimize multiple spatial queries which w ill be w idely used in IoT, because most of them have focused on a single spatial query optimization. Therefore, we propose a new multiple spatial query optimization algorithm which can energy-efficiently process multiple spatial queries in a sensor network. The algorithm uses a concept of 'query merging' that performs the merged set after merging multiple spatial queries located at adjacent area. Here, our algorithm makes a decision on which is better between the merged and the separate execution of queries. For such the decision making, we additionally propose the cost estimation method on the spatial query execution. Finally, we analyze and clarify our algorithm's distinguished features using the spatial indexing methods of GR-tree, SPIX, CPS.