• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1347-1355
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• 2007

A sensor network is composed of a large number of tiny devices, scattered and deployed in a specified regions. Each sensing device has processing and wireless communication capabilities, which enable it to gather information from the sensing area and to transfer report messages to a base station. The energy-efficient routing paths are established when the base station requests a query, since each node has several characteristics such as low-power, constrained energy, and limited capacity. The established paths are recovered while minimizing the total transmit energy and maximizing the network lifetime when the paths are broken. In this paper, we propose a routing algorithm that each sensor node reports its adjacent link information to the sink node when a sink node broadcasts a query. The sink node manages the total topology and establishes routing paths. This algorithm has a benefit to find an alternative path by reducing the negotiating messages for establishing paths when the established paths are broken. To reduce the overhead of collection information, each node has a link information before reporting to the sink. Because the node recognizes which nodes are adjacent. The proposed algorithm reduces the number of required messages, because sensor nodes receive and report routing messages for establishment at the beginning of configuring routing paths, since each node keeps topology information to establish a routing path, which is useful to report sensing tasks in monitoring environments.

• Journal of KIISE:Databases
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• v.34 no.1
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• pp.59-69
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• 2007

The trajectory of a tag in RFID system is represented as a interval that connects two spatiotemporal locations captured when the tag enters and leaves the vicinity of a reader. Whole trajectories of a tag are represented as a set of unconnected interval because the location of the tag which left the vicinity of a reader is unknown until it enters the vicinity of another reader. The problems are that trajectories of a tag are not connected. It takes a long time to find trajectories of a tag because it leads to searching the whole index. To solve this problem, we propose a technique that links two intervals of the tag and an index scheme called SLR-tree. We also propose a sharing technique of link information between two intervals which enhances space utilization of nodes, and propose a split policy that preserves shared-link information. And finally, we evaluate the performance of the proposed index and prove that the index processes history queries efficiently.

• The KIPS Transactions:PartC
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• v.18C no.5
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• pp.361-368
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• 2011

In this study, we present a method for efficiently aggregating networks state information required to determine feasible paths in transport networks that uses the source routing algorithm for hierarchical QoS routing. It is proposed to transform the full mesh topology whose Service Boundary Line serves as its logical link into the star topology. This is an aggregation method that can be used when there are two or more QoS parameters for the link to be aggregated in an asymmetric network, and it improves the information accuracy of the star topology. For this purpose, the Service Boundary Line's 3 attributes, splitting, joining and integrating, are defined in this study, and they are used to present a topology transformation method. The proposed method is similar to space complexity and time complexity of other known techniques. But simulation results showed that aggregated information accuracy and query response accuracy is more highly than that of other known method.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.202-214
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• 2005

The semantic web is the web paradigm that represents not general link of documents but semantics and relation of document. In addition it enables software agents to understand semantics of documents. We propose a semantic search based on inference with ontologies, which has the following characteristics. First, our search engine enables retrieval using explicit ontologies to reason though a search keyword is different from that of documents. Second, although the concept of two ontologies does not match exactly, can be found out similar results from a rule based translator and ontological reasoning. Third, our approach enables search engine to increase accuracy and precision by using explicit ontologies to reason about meanings of documents rather than guessing meanings of documents just by keyword. Fourth, domain ontology enables users to use more detailed queries based on ontology-based automated query generator that has search area and accuracy similar to NLP. Fifth, it enables agents to do automated search not only documents with keyword but also user-preferable information and knowledge from ontologies. It can perform search more accurately than current retrieval systems which use query to databases or keyword matching. We demonstrate our system, which use ontologies and inference based on explicit ontologies, can perform better than keyword matching approach .

• Journal of Digital Contents Society
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• v.11 no.3
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• pp.357-365
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• 2010

Personalized web search engine provides personalized results to users by query expansion, re-ranking or other methods representing user's intention. The personalized result page includes URL, page title and small text fragment of each web document. which is known as snippet. The snippet is the summary of the document which includes the keywords issued by either user or search engine itself. Users can verify the relevancy of the whole document using only the snippet, easily. The document summary (snippet) is an important information which makes users determine whether or not to click the link to the whole document. Hence, if a search engine generates personalized document summaries, it can provide a more satisfactory search results to users. In this paper, we propose a personalized document summary system for personalized web search engines. The proposed system provides increased degree of satisfaction to users with marginal overhead.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.4
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• pp.663-670
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• 2017

The purpose of this study is to define On-line Video Syllabus Template which is based on adaptive mode with interaction.A syllabus has the significance as a teaching and learning plan. However, it has not only been considered as a formal document, has also been limited into a simple query since it has been made into a fragmentary structure, lacking of link between other services and reuse. Additionally, this paper is aimed to design three-dimensional syllabus which makes it possible to provide students with practical information related to teaching and learning and share it with teachers and students. The following is the technique proposed in this paper. It is made to be served for the Syllabus centered on teaching and learning, which is including the definition of hierarchy structure, the media contents application according to the learner's preference and real-time variation function. On-line Video Syllabus provided through LMS has availability and credibility of teaching and learning, in that it enable increased utilization by strengthening convenience.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3168-3186
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• 2020

Automatic topic essay generation (TEG) is a controllable text generation task that aims to generate informative, diverse, and topic-consistent essays based on multiple topics. To make the generated essays of high quality, a reasonable method should consider both diversity and topic-consistency. Another essential issue is the intrinsic link of the topics, which contributes to making the essays closely surround the semantics of provided topics. However, it remains challenging for TEG to fill the semantic gap between source topic words and target output, and a more powerful model is needed to capture the semantics of given topics. To this end, we propose a pretraining-based contextual self-attention (PC-SAN) model that is built upon the seq2seq framework. For the encoder of our model, we employ a dynamic weight sum of layers from BERT to fully utilize the semantics of topics, which is of great help to fill the gap and improve the quality of the generated essays. In the decoding phase, we also transform the target-side contextual history information into the query layers to alleviate the lack of context in typical self-attention networks (SANs). Experimental results on large-scale paragraph-level Chinese corpora verify that our model is capable of generating diverse, topic-consistent text and essentially makes improvements as compare to strong baselines. Furthermore, extensive analysis validates the effectiveness of contextual embeddings from BERT and contextual history information in SANs.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.53-55
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• 2000

Xenie is the JAVA application software that integrates and represents 'gene to function'information of human gene. Xenie extracts data from several heterogeneous molecular biology databases and provides integrated information in human readable and machine usable way. We defined 7 semantic frame classes (Gene, Transcript, Polypeptide, Protein_complex, Isotype, Functional_object, and Cell) as a common schema for storing and integrating gene to function information and relationship. Each of 7 semantic frame classes has data fields that are supposed to store biological data like gene symbol, disease information, cofactors, and inhibitors, etc. By using these semantic classes, Xenie can show how many transcripts and polypeptide has been known and what the function of gene products is in General. In detail, Xenie provides functional information of given human gene in the fields of semantic objects that are storing integrated data from several databases (Brenda, GDB, Genecards, HGMD, HUGO, LocusLink, OMIM, PIR, and SWISS-PROT). Although Xenie provide fully readable form of XML document for human researchers, the main goal of Xenie system is providing integrated data for other bioinformatic application softwares. Technically, Xenie provides two kinds of output format. One is JAVA persistent object, the other is XML document, both of them have been known as the most favorite solution for data exchange. Additionally, UML designs of Xenie and DTD for 7 semantic frame classes are available for easy data binding to other bioinformatic application systems. Hopefully, Xenie's output can provide more detailed and integrated information in several bioinformatic systems like Gene chip, 2D gel, biopathway related systems. Furthermore, through data integration, Xenie can also make a way for other bioiformatic systems to ask 'function based query'that was originally impossible to be answered because of separatly stored data in heterogeneous databases.

• Journal of Information Management
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• v.40 no.1
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• pp.133-156
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• 2009

In this study, we link informal Web resources to KISTI NDSL's collections using automatic semantic indexing and tagging to examine the possibility of the service which recommends related documents using the similarity between KISTI's formal information resources and informal web resources. We collect and index Web resources and make automatic semantic linking through STEAK with KISTI's collections for NDSL retrieval. The macro precision which shows retrieval precision per a subject category is 62.6% and the micro precision which shows retrieval precision per a query is 66.9%. The experts' evaluation score is 76.7. This study shows the possibility of semantic linking NDSL retrieval results with Web information resources and expanding information services' coverage to informal information resources.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.1-7
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• 2023

Deep web collection means entering a query in a search form and collecting response results. It is estimated that the information possessed by the deep web has about 450 to 550 times more information than the statically constructed surface web. The static method does not show the changed information until the web page is refreshed, but the dynamic web page method updates the necessary information in real time and provides real-time information without reloading the web page, but crawler has difficulty accessing the updated information. Therefore, there is a need for a way to automatically collect information on these deep webs using a crawler. Therefore, this paper proposes a method of utilizing scripts as general links, and for this purpose, an algorithm that can utilize client scripts like regular URLs is proposed and experimented. The proposed algorithm focused on collecting web information by menu navigation and script execution instead of the usual method of entering data into search forms.