• International Journal of Knowledge Content Development & Technology
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• v.10 no.2
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• pp.7-18
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• 2020

Communication is a process involving a group of interrelated elements working together for the purpose of information transfer. This paper discusses information retrieval as a communication process in the 21st century library. The difficulties associated with access to recorded knowledge through bibliographic control devices have been exacerbated by the interposition of additional encoding processes in the library and further decoding by the users. In addition, the innovation of internet/web has revolutionized the means and mode of communication process in the library by flooding information seekers with information and creating an illusion of self-sufficiency in many users. With these changes in information seeking behaviour and pattern, a cybernetic approach to information retrieval has emerged emphasizing adaptive control mechanisms and feedback processes. This paper argues that libraries should strive to continuously remain relevant by keeping abreast with changes in the behavior of information users. To this end, this paper proposes apomediatic-cybernetic model of communication, which illustrates information retrieval processes for the 21st-century library.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.476-479
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• 2005

The information available on the Internet has become widely used, primarily due to the ability of Web based E-Commerce and M-Commerce Retrieval Engines to find useful information for users. However, present day Commerce Retrieval Engines are far from perfect because they return results based on simple user keyword matches without any regard for the concepts in which the user is interested. In this thesis, we design and evaluate a Recommender system for web context aware based information retrieval using user profiles. Also, we designed personalization framework in ubiquitous environment based both e-commerce and m-commerce and presented the interaction of user profile including User XQuery pattern in semantic web.

• 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 Society of Computer and Information
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• v.15 no.4
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• pp.1-9
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• 2010

In the new generation of Web, commonly called "Web 2.0", blogging has facilitated the publishing information or his/her opinion on the web. Various blog retrieval algorithms have been proposed to search for blogs more effectively. However, actually keyword-based searching or link-analysis blog ranking system cannot satisfy the user's requirement. In this paper, we suggest a topic-based weighting blog retrieval system in which the links between blog writings and searching words are considered to improve the search results. Our system extracts topics from each blog and weights them much higher than other guide words. In the comparison with other systems, we see that the proposed topic-base system has better recall rate of search results.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.1103-1111
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• 2003

Information retrieval system with indexing system matching single keyword is simple and popular. But with single keyword matching it is very hard to represent the exact meaning of documents and the set of documents from retrieval is very large, therefore it can't satisfy the user of the information retrieval systems. This paper proposes a phrase-based indexing system based on the phrase, the larger syntax unit than a single keyword. Web documents include lots of syntactic errors, the natural language parser with high Quality cannot be expected in Web. Partial trees, even not a full tree, from fully bottom-up parsing is still useful for extracting phrases, and they are much more discriminative than single keyword for index. It helps the information retrieval system enhance the efficiency and reduce the processing overhead.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.3
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• pp.103-110
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• 2008

This paper proposes an effective keyword extraction method for the Web videos. The proposed method classifies the Web video pages in one of 4 types. As such, we analyzed the structure of the Web pages based on the number of videos and the layout of the Web pages. And then we applied the keyword extraction algorithm fit to each page type. The experiment with 1,087 Web pages that have total 2,462 videos showed that the recall of the proposed extraction method is 18% higher than ImagerRover[2]. So, the proposed method could be used to build a powerful video search system for WWW.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1491-1499
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• 2011

Now a days, to make good use of tags is a general tendency when users need to upload or search some multimedia data such as images and videos on the Web. In this paper, we introduce an approach to calculate semantic importance of tags and to make re-ranking with them on tagged Web image retrieval. Generally, most photo images stored on the Web have lots of tags added with user's subjective judgements not by the importance of them. So they become the cause of precision rate decrease with simple matching of tags to a given query. Therefore, if we can select semantically important tags and employ them on the image search, the retrieval result would be enhanced. In this paper, we propose a method to make image retrieval re-ranking with the key tags which share more semantic information with a query or other tags based on Wikipedia-based semantic relatedness. With the semantic relatedness calculated by using huge on-line encyclopedia, Wikipedia, we found the superiority of our method in precision and recall rate as experimental results.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.169-180
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• 2009

The conventional paper retrieval is the keyword-based search and as a huge amount of data be published, this search becomes more difficult in retrieving information that user want to find. In order to search for information to the user's intent, we need to introduce semantic Web that represents semantics of Web document resources on the Internet environment as ontology and enables the computer to understand this ontology. Therefore, we describe a paper retrieval system through OWL(Ontology Web Language) ontology-based reason in this paper. We build the paper ontology based on OWL which is new popular ontology language for semantic Web and represent the correlation among diverse paper properties as the DL(description logic) query, and then this system infers the correct results from the paper ontology by using the DL query and makes it possible to retrieve information intelligently. Finally, we compared our experimental result with the conventional retrieval.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.25-34
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• 2009

As the trend of the Web is changing toward 'Web 2.0', OpenAPIs, Web 2.0's core technology, are used in many web sites. In the past, services in websites are used in its own, but recently it is possible to use services in other websites by using OpenAPI. In u-GIS many vendors also can provide combined service by using OpenAPI. There are already lots of OpenAPIs and the numer of OpenAPI increases very fast. So it is difficult to find a service that we want to use, and also difficult to find services for mashup. In this paper, we developed retrieval methods for OpenAPIs and mashup capable services based on similarity. First we define the integrated service information model to cover various protocols of OpenAPI, then developed a retrieval methods based on it. By implementing system according these methods by using relational database and JSP, we prove that the system can provide an ranked result sets based on similarity, OpenAPI's integration retrieval results and mashup capable service retrieval results.

• Journal of Internet Computing and Services
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• v.2 no.1
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• pp.49-61
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• 2001

Internet has been becoming widely popular and making rapid progress and network technologies is showing extension in data transmission speeds. Rapid and convenient multimedia services supplied with high quality and high speed are being needed, This paper treats of the design and implement method of clip-based video retrieval system on the world-wide-web environments. The implemented system consists of the content-based indexing system supporting convenient services for video contents providers and the web-based retrieval system in order to make it easy and various information retrieval for users on the world-wide-web. Three important methods were used in the content-based indexing system. Key frame extracting method by dividing video data, clip file creation method by clustering related information and video database build method by using clip unit, In web-based retrieval system, retrieval method by using a key word, two dimension browsing method of key frame and real-time display method of the clip were used. As a result. the proposed methodologies showed a usefulness of video content providing. and provided an easy method for searching intented video content.