• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.923-926
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• 2010

A sensor network system processes user queries using the recent field data collected by each sensor node. To process user queries, the system propagates the queries to the specific sensor nodes which have the relevant data and aggregates the results of the queries. However, if continuous queries are processed by the existing scheme, the system has the problem where the queries are propagated repeatedly. In this paper, we propose the query processing scheme to process the continuous queries over the sensor streaming data. To do this, each sensor node builds its own query index on its node. And, we present the scheme to deal with the unexpected data rising on the sensor node.

• Journal of KIISE
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• v.44 no.1
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• pp.1-12
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• 2017

The continuously growing internet service requirements has resulted in a multitier system structure consisting of web server and database (DB) server. In this multitier structure, the existing intrusion detection system (IDS) detects known attacks by matching misused traffic patterns or signatures. However, malicious change to the contents at DB server through hypertext transfer protocol (HTTP) requests at the DB server cannot be detected by the IDS at the DB server's end, since the DB server processes structured query language (SQL) without knowing the associated HTTP, while the web server cannot identify the response associated with the attacker's SQL query. To detect these types of attacks, the malicious user is tracked using knowledge on interaction between HTTP request and SQL query. However, this is a practical challenge because system's source code analysis and its application logic needs to be understood completely. In this study, we proposed a scheme to find the HTTP request associated with a given SQL query using only system log files. We first generated an HTTP request-SQL query map from system log files alone. Subsequently, the HTTP request associated with a given SQL query was identified among a set of HTTP requests using this map. Computer simulations indicated that the proposed scheme finds the HTTP request associated with a given SQL query with 94% accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.810-813
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• 2004

Indexing and Retrieving images from large and varied collections using image content as a key is a challenging and important problem in computer vision application. In this paper, a color Content-based Image Retrieval (CBIR) system using hierarchical Region of Interest (ROI) query and indexing is presented. During indexing process, First, The ROIs on every image in the image database are extracted using a region-based image segmentation technique, The JSEG approach is selected to handle this problem in order to create color-texture regions. Then, Color features in form of histogram and correlogram are then extracted from each segmented regions. Finally, The features are stored in the database as the key to retrieve the relevant images. As in the retrieval system, users are allowed to select ROI directly over the sample or user's submission image and the query process then focuses on the content of the selected ROI in order to find those images containing similar regions from the database. The hierarchical region-of-interest query is performed to retrieve the similar images. Two-level search is exploited in this paper. In the first level, the most important regions, usually the large regions at the center of user's query, are used to retrieve images having similar regions using static search. This ensures that we can retrieve all the images having the most important regions. In the second level, all the remaining regions in user's query are used to search from all the retrieved images obtained from the first level. The experimental results using the indexing technique show good retrieval performance over a variety of image collections, also great reduction in the amount of searching time.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.140-152
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• 2003

An XML document has a structure which may be irregular. It is difficult for end-users to comprehend the irregular document structure exactly. For these XML documents, an end-user has a difficulty in using structured query. Therefore, an end-user formulates no structured query or a query which has a little structure information. In this context, we propose new retrieval models which use the structured information for ranking and compensate the difference between user query structure and document structure. To ease with querying, we assume the independence among querying paths which represent structural constraints. Since this assumption makes degradation of the expression power of a query language, we also propose a model which overcome this problem. As there had been no test collections for XML documents, we made a small test collection from TIPSTER of the RTEC and experimented on this collection without a structured query, From this experiment, we showed that our models improve average precision about 67% over conventional Vector-Space model.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.35-44
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• 2011

Ontologies are playing an important role in semantic web which is emerging as a next stage of the web revolution because various kinds of metadata are described in ontologies. Correspondingly, many query languages like SPARQL, RDQL etc. have been proposed for querying these ontologies. But users have to know the structures and resource names of ontologies completely to get search results even if they have expertise on complex formal logic and syntax of the query languages. Especially, casual users do not know the resource names and may use different words from resource names when they write their query language. This vocabulary gap problem have to be solved to raise the success rate. In this paper, an approach for translating user's search words to corresponding resource names has been proposed. This approach uses semantic similarity between user created search words and ontology resource names.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3087-3103
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• 2022

Nearest neighbor query in location-based services has become a popular application. Aiming at the shortcomings of the privacy protection algorithms of traditional ciphertext nearest neighbor query having the high system overhead because of the usage of the double Hilbert curves and having the inaccurate query results in some special circumstances, a privacy protection algorithm of ciphertext nearest neighbor query which is based on the single Hilbert curve has been proposed. This algorithm uses a single Hilbert curve to transform the two-dimensional coordinates of the points of interest into Hilbert values, and then encrypts them by the order preserving encryption scheme to obtain the one-dimensional ciphertext data which can be compared in numerical size. Then stores the points of interest as elements composed of index value and the ciphertext of the other information about the points of interest on the server-side database. When the user needs to use the nearest neighbor query, firstly calls the approximate nearest neighbor query algorithm proposed in this paper to query on the server-side database, and then obtains the approximate nearest neighbor query results. After that, the accurate nearest neighbor query result can be obtained by calling the precision processing algorithm proposed in this paper. The experimental results show that this privacy protection algorithm of ciphertext nearest neighbor query which is based on the single Hilbert curve is not only feasible, but also optimizes the system overhead and the accuracy of ciphertext nearest neighbor query result.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.53-60
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• 2012

In this paper, we proposes a new document summarization method using the expanded query by wikipedia and the semantic feature representing inherent structure of document set. The proposed method can expand the query from user's initial query using the relevance feedback based on wikipedia in order to reflect the user require. It can well represent the inherent structure of documents using the semantic feature by the non-negative matrix factorization (NMF). In addition, it can reduce the semantic gap between the user require and the result of document summarization to extract the meaningful sentences using the expanded query and semantic features. The experimental results demonstrate that the proposed method achieves better performance than the other methods to summary document.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.2
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• pp.280-285
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• 2007

This paper proposes a technique improving performance using word senses and user feedback in web information retrieval, compared with the retrieval based on ambiguous user query and index. Disambiguation using word senses is very important processing for improving performance by eliminating the irrelevant pages from the result. According to semantic categories of nouns which are used as index for retrieval, we build the word sense knowledge-base and categorize the web pages. It can improve the performance of retrieval system with user feedback deciding the query sense and information seeking behavior to web pages.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1626-1633
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• 2010

In this paper, we implemented medicinal plant information system based on user requirement using Ajax technique which can retrieve data from the server asynchronously in the background without refresh webpage and jQuery which is a lightweight cross-browser javascript library. Also, we presented the source code handling the server response data used in the system and compared the features by the type of response data. This system shows the improvement of user interaction and response rates because of a simple response data from the server, client-side data processing and change of web page by manipulating the DOM tree and provides ease of use and convenient data access.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.467-470
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• 2003

When user wants to find objects which have the nearest position from him, we use the nearest neighbor (NN) query. The GIS applications, such as navigation system and traffic control system, require processing of NN query for moving objects (MOs). MOs have trajectory with changing their position over time. Therefore, we should be able to find NN object continuously changing over the whole query time when process NN query for MOs, as well as moving nearby on trajectory of query. However, none of previous works consider trajectory information between objects. Therefore, we propose a method of continuous NN query for trajectory of MOs. We call this CTNN (continuous trajectory NN) technique. It ran find constantly valid NN object on the whole query time by considering of trajectory information.