• Spatial Information Research
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• v.21 no.4
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• pp.35-45
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• 2013

Most multimedia contains location information whether they are implicit or explicitly, and which are very useful for several purposes. In particular, we may use location information in defining query conditions to retrieve relevant multimedia. For this reason, a number of works have been done to organize and retrieve geo-referenced multimedia data. However, they mostly focus on outdoor space where position is identified by (x, y, z) coordinates. In this paper, we focus on multimedia in an alternative space, indoor space, which differs from outdoor space in several aspects. First indoor space is considered as symbolic space, where location is identified by a symbolic code such as room number rather than coordinates. Second, topological information is a crucial element in providing indoor spatial information services. Third, indoor space is in more micro-scale than outdoor space, which influences on determining the visibility of cameras. Based on these different characteristics of indoor space, we survey the requirements of management systems of indoor geo-referenced multimedia. Then we propose a geo-coding scheme for multimedia in indoor space as an extension of IndoorGML, an OGC(Open Geospatial Consortium) candidate standard for indoor spatial information. We also present a prototype system called, IngC (INdoor Geo-Coding) developed to store and manage indoor geo-referenced multimedia.

• The KIPS Transactions:PartA
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• v.10A no.2
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• pp.93-100
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• 2003

With the advent of distributed computing and Web service technologies, lots of users have been requiring services that can conveniently obtain and/or support well-assembled information based on Web. For this reason, we are to construct Automatic Linking Support Systems for generating Web-based integrated information and supporting retrieval information according to user's various requirements. Our system organization is based on client/server system. A server environment consisted of automatic linking engine that can provide lexical analyzing, query processing and integrated document generating functions, and databases that are made of dictionaries, image and URL contents. Also, client environments consisted of Web editor that can generate integrated documents and Web helper that can retrieve them via automatic linking engine and databases. For client's user-friendly interfaces, web editor and helper programs can directly execute by down leading from a server without setup them before inside clients. For reducing server's overheads, Parts of server's executing modules are distributed to clients on which they can be executing. As an implementation of our system, we use the JDK 1.3, SWING for user interfaces like Web editor and helper, RMI mechanism for interaction between clients and a server, and SQL server 7.0 for database development, respectively. Finally, we showed the access procedures of automatic document linking engine and databases from Web editor or Web helper, and results appearing on their screens.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.495-508
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• 2004

Recently, in content-based music information retrieval systems, to enhance the response time of retrieving music data from large music database, some researches have adopted the indexing mechanism that extracts and indexes the representative melodies. The representative melody of music data must stand for the music itself and have strong possibility to use as users' input queries. However, since the previous researches have not considered the musical composition forms, they are not able to correctly catch the contrast, repetition and variation of motif in musical forms. In this paper, we use an index automatically constructed from representative melodies such like first melody, climax melodies and similarly repeated theme melodies. At first, we expand the clustering algorithm in order to extract similarly repeated theme melodies based on the musical composition forms. If the first melody and climax melodies are not included into the representative melodies of music by the clustering algorithm, we add them into representative melodies. We implemented a prototype system and did experiments on comparison the representative melody index with other melody indexes. Since, we are able to construct the representative melody index with the lower storage by 34％ than whole melody index, the response time can be decreased. Also, since we include first melody and climax melody which have the strong possibility to use as users' input query into representative melodies, we are able to get the more correct results against the various users' input queries than theme melody index with the cost of storage overhead of 20％.

• The KIPS Transactions:PartA
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• v.17A no.5
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• pp.229-236
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• 2010

With an increasing number of documents in the Internet or enterprises, it becomes crucial to efficiently support users' queries on those documents. In that situation, the full-text search technique is accepted in general, because it can answer uncontrolled ad-hoc queries by automatically indexing all the keywords found in the documents. The size of index files made for full-text searches grows with the increasing number of indexed documents, and thus the disk cost may be too large to process multi-keyword queries against those enlarged index files. To solve the problem, we propose both of the index file structure and its management scheme suitable to the processing of multi-keyword queries against a large volume of index files. For this, we adopt the structure of inverted-files, which are widely used in the multi-keyword searches, as a basic index structure and modify it to a hierarchical structure for join operations and ranking operations performed during the query processing. In order to save disk costs based on that index structure, we dynamically store in the main memory the results of join operations between two keywords, if they are highly expected to be entered in users' queries. We also do performance comparisons using a cost model of the disk to show the performance advantage of the proposed scheme.

• Spatial Information Research
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• v.18 no.2
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• pp.57-65
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• 2010

Users often visit many stores while comparing the products for purchasing products or products related to it. Given a service providing location information of these stores, users can make their purchase efficiently because of reducing the time and effort they spent for wandering around and obtaining new purchase opportunities by knowing a kind of relevant stores near there. In this paper, for the purpose of providing relevant stores information efficiently, we suggest an Ambient Service Model that consists of three layers: "structured(purchase-related) information space", "real space", and "ambient information space". In the model, stores information collected from the web is grouped and structured automatically by relationships in terms of purchase. And users search relevant stores information by using an Ambient Query that is created by their context in real space. Finally, users obtain relevant stores information that is in the form of hierarchy structure on map interface. Then, users can search other kinds of relevant stores information additionally by using hierarchy structure. Consequently, It is possible to develope a service that users can obtain relevant stores information intuitively without complex search processes through the model. Also, we expect that the model can be used for developing services that provide objects information related to various objects besides stores.

• Spatial Information Research
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• v.18 no.2
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• pp.67-75
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• 2010

When people are shopping at a large shopping mall, they usually become to go around many stores for looking for better products and comparing them. In this paper, we design and implement a purchasing activity support system based on an Ambient Service Model that provides relevant stores information on map interface hierarchically through user contexts based search, to support such user's purchasing activities with the help of relevant information. In this system, users can search for relevant stores information through the system by Ambient Query which is created by their location and stores information with a mobile device. Then, users obtain relevant stores information provided in the form of hierarchy of keywords as a highly condensed summary and easily figure out the locations of the stores on a map interface. Moreover, users search additional other kinds of relevant stores information over the hierarchy of keywords. Eventually, users can obtain relevant stores information intuitively and conveniently without complex search processes. We implemented this system by integrating the subordinate technologies such as RFID, map-based, location-based and ontology technology. We also performed experiments on a well-known shopping region (Ilsan Lapesta shopping mall, Goyang-city Gyeonggi-do, Korea). Finally, we also confirmed that users' shopping activities were significantly improved by utility the present system.

• Journal of the Korea Society of Computer and Information
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• v.18 no.1
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• pp.137-147
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• 2013

The RFID(Radio Frequency Identification) and the WSN(Wireless Sensor Network) have technical similarities and mutual effects, they have been recognized to be studied separately, and sufficient studies have not been conducted on the technical integration of the RFID and the WSN. Therefore, EPC global which realized the issue proposed the EPC(Electronic Produce Code) Sensor Network to efficiently integrate and interoperate the RFID and WSN technologies based on the international standard EPC global network. The proposed EPC Sensor Network technology uses the Complex Event Processing method in the middleware to integrate data occurring through the RFID and the WSN in a single environment and to interoperate the events based on the EPC global network. However, as the EPC Sensor Network technology continuously performs its operation even in the case that the minimum conditions are not to be met to find complex events in the middleware, its operation cost rises. Therefore, to address the problems of the existing system, we defined the minimum conditions of the complex events to detect unnecessary complex events in the middleware, and proposed an algorithm that can extract complex events only when the minimum conditions are to be met. To examine the minimum conditions, a index and a query index are used to extract complex events. To evaluate the performance of the proposed methods, In the case of the method of extracting complex events based on a bitmap index, we used the existing extraction method and NS2 simulation to evaluate its performance and thus to show its good performance in terms of the number of operation and the processing time for the complex events.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.163-172
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• 2012

Collaborative filtering which is used explicit method in a existing recommedation system, can not only reflect exact attributes of item but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. This paper proposes the personalized recommendation system using RFM method and k-means clustering in u-commerce which is required by real time accessablity and agility. In this paper, using a implicit method which is is not used complicated query processing of the request and the response for rating, it is necessary for us to keep the analysis of RFM method and k-means clustering to be able to reflect attributes of the item in order to find the items with high purchasablity. The proposed makes the task of clustering to apply the variable of featured vector for the customer's information and calculating of the preference by each item category based on purchase history data, is able to recommend the items with efficiency. To estimate the performance, the proposed system is compared with existing system. As a result, it can be improved and evaluated according to the criteria of logicality through the experiment with dataset, collected in a cosmetic internet shopping mall.

• Journal of Intelligence and Information Systems
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• v.15 no.2
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• pp.49-59
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• 2009

Contents-based image retrieval methods are in general more objective and effective than text-based image retrieval algorithms since they use color and texture in search and avoid annotating all images for search. SIM(Self-organizing Image browsing Map) is one of contents-based image retrieval algorithms that uses only browsable mapping results obtained by SOM(Self Organizing Map). However, SOM may have an error in selecting the right BMU in learning phase if there are similar nodes with distorted color information due to the intensity of light or objects' movements in the image. Such images may be mapped into other grouping nodes thus the search rate could be decreased by this effect. In this paper, we propose an improved SIM that uses HSV color model in extracting image features with color quantization. In order to avoid unexpected learning error mentioned above, our SOM consists of two layers. In learning phase, SOM layer 1 has the color feature vectors as input. After learning SOM Layer 1, the connection weights of this layer become the input of SOM Layer 2 and re-learning occurs. With this multi-layered SOM learning, we can avoid mapping errors among similar nodes of different color information. In search, we put the query image vector into SOM layer 2 and select nodes of SOM layer 1 that connects with chosen BMU of SOM layer 2. In experiment, we verified that the proposed SIM was better than the original SIM and avoid mapping error effectively.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.476-493
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• 2003

Data broadcast is an effective data transmission method from a data base server to numerous mobile clients due to the restrictions on mobile environment such as low wireless communication bandwidth and energy shortage of mobile devices. There are various broadcast methods based on clients' data access frequencies or semantic relationship of data. The broadcast schedule based only on the access frequencies does not consider semantic relations of data, so that when a client needs to access a series of semantically related data, the client has to listen to the wireless channel for a long time. On the other hand, the broadcast schedule based only on semantic relationship of data makes data access time longer when clients highly request specific data which are not semantically related but frequently accessed. In this paper, we present an efficient data broadcast method based on not only data access frequencies but also semantic relationship to improve mobile clients' query response time. The new hybrid broadcast method we propose creates a data broadcast schedule according to the data access frequencies and then the schedule is adjusted to reflect semantic relationship of data. We show our method is efficient by experimental performance analysis.