• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.345-348
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• 2005

Because the current web search engine estimates the similarity of documents, using the frequency of words, many documents irrespective of the user query are provided. To solve these kinds of problems, the semantic web is appearing as a future web. It is possible to provide the service based on the semantic web through ontology which specifies the knowledge in a special domain and defines the concepts of knowledge and the relationships between concepts. In this paper to search the information of potential customers for home-delivery marketing, we model the specific domain for generating the ontology. And we research how to retrieve the information, using the ontology. Therefore, in this paper, we generate the ontology to define the domain about potential customers and develop the search robot which collects the information of customers.

• Archives of design research
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• v.15 no.2
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• pp.223-232
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• 2002

As the Internet becomes widespread as a significant tool of obtaining information, there is a growing demand for a system to efficiently organize and manage information on the Internet. Accordingly, research on the directory classification structure that directly affects the efficiency of a users information search is actively investigated in every field. The study intends to suggest an efficient classification structure by comparing and analyzing the directory classification structure of current design portal sites with the theory of literature classification structure, in order to increase the efficiency of search according to the directory classification structure of design sector.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.144-147
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• 2015

Question Answering (QA) services can provide exact answers to user questions written in natural language form. This research focuses on how to build a QA system for a specific domain area. Online and offline QA system architecture of targeted domain such as domain detection, question analysis, reasoning, information retrieval, filtering, answer extraction, re-ranking, and answer generation, as well as data preparation are presented herein. Test results with an official Frequently Asked Question (FAQ) set showed 68% accuracy of the top 1 and 77% accuracy of the top 5. The contribution of each part such as question analysis system, document search engine, knowledge graph engine and re-ranking module for achieving the final answer are also presented.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.693-696
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• 2007

대규모 데이터를 효율적으로 검색하기 위한 병렬 정보검색 시스템에서는 하드웨어 확장으로 인한 병렬화로 시스템 전체의 작업 처리량을 증가시켰다. 그러나 병렬 시스템 상에서 수행되는 검색엔진의 알고리즘들은 여전히 순차적으로 수행되기 때문에, 사용자의 개별적인 질의처리 시간은 단축되지 않는다. 본 연구는 검색엔진의 병렬화를 위하여 사용자 질의처리 과정과 역색인 파일처리 과정의 순차 알고리즘들을 조사하여 병렬화의 필요성과 가능성을 평가한다. 이러한 평가는 병렬 정보검색 시스템에서 수행되는 순차 알고리즘들의 효과적이고 체계적인 병렬화를 도모하고, 보다 효율적인 병렬 정보검색 시스템의 구축을 가능하게 한다.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.54-62
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• 2009

To avoid the redundant investment on the project selection process, it is necessary to check whether the submitted research topics have been proposed or carried out at other institutions before. This is possible through the search engines adopted by the keyword matching algorithm which is based on boolean techniques in national-sized research results database. Even though the accuracy and speed of information retrieval have been improved, they still have fundamental limits caused by keyword matching. This paper examines implemented TFIDF-based algorithm, and shows an experiment in search engine to retrieve and give the order of priority for similar and redundant documents compared with research proposals, In addition to generic TFIDF algorithm, feature weighting and K-Nearest Neighbors classification methods are implemented in this algorithm. The documents are extracted from NDSL(National Digital Science Library) web directory service to test the algorithm.

• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.19-29
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• 2013

In the current Internet environment where there is high space complexity of information, search engines aim to provide accurate information that users want. But content-based method adopted by most of search engines cannot be used as an effective tool in the current Internet environment. As content-based method gives different weights to each web page using morphological characteristics of vocabulary, the method has its drawbacks of not being effective in distinguishing each web page. To resolve this problem and provide useful information to the users, this paper proposes an evaluation method based on categories. Category-based evaluation method is to extend query to semantic relations and measure the similarity to web pages. In applying weighting to web pages, category-based evaluation method utilizes user response to web page retrieval and categories of query and thus better distinguish web pages. The method proposed in this paper has the advantage of being able to effectively provide the information users want through search engines and the utility of category-based evaluation technique has been confirmed through various experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.772-774
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• 2017

Currently, there are many simple searches for local culture and tourism, but systematic information retrieval using ontology technology is weak. The keyword-based search, which is an existing search method, derives a search result that is different from a user's wanted intention. On the other hand, semantic search using ontology constructs shows the information related to the search term by creating a relation between words and words. Therefore, when tourists search for cultural and tourist attractions in the area, they provide information that includes meaning relevance in the search results. If the ontology provides information on the culture, sightseeing area, transportation, Can be more easily grasped. In this paper, we propose an ontology-based retrieval system based on culture and tourist sites utilizing public institutions database by using mobile application by extending search system which relied only on existing internal database to provide accurate and reliable information to users. This efficient structure of the ontology makes it possible to provide information suitable for the user quickly and accurately.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.75-77
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• 2021

A variety of search engines are currently in use. The search engine supports the retrieval of data required by users through three stages: crawling, index generation, and output of search results based on meta-tag information. However, a large number of documents obtained by searching for keywords are often unrelated or scarce. Because of these problems, it takes time and effort to grasp the content from the search results and classify the accuracy. The index of search engines is updated periodically, but the criteria for weighted values and update periods are different from one search engine to another. Therefore, this paper uses the LSTM model, which extracts the relationship between keywords entered by the user and documents instead of the existing search engine, and improves the relationship between keywords and documents by entering keywords that the user wants to find.

• Journal of the Korean Society for information Management
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• v.17 no.1
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• pp.103-127
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• 2000

This study compared finding economic and energy information on the WWW to finding the same information on DIALOG, a traditional search service. Professional searchers answered 20 questions for end users using either of DIALOG and one Internet database (general search engine or Web database). The relevance of the results in both sets of answers was ranked by searchers and end-users, respectively. The study found that searching for information on the Web took at least twice as long as it did when using DIALOG. Relevance rating was a little higher for materials found on DIALOG. However, the relevance rating difference between two systems was not so higher than we expected. From the research results, we conclude that Internet database including Web database and general search engines is providing valuable information of economic and energy subject areas.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.209-217
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• 2019

In this paper, the purpose of this paper is to lay the foundation for the search system by using and building an online search engine suitable for the search domain and enabling search, conversion, integration and sharing of information. It is to use the ontology to infer hierarchical relationships, deduce objects based on that layer, and extract attributes to search areas that are relevant to the data that the user wants. In order to search for information in this way, the information search system was implemented by entering key words related to 'qualifications'. The implemented system arranged the meaning and relationship of each attribute online so that the general public can search information quickly, easily, and accurately. In addition, the implementation results were compared with two different search engines. Comparable search engines are Naver and Daum, the two major search engines. The search engine of this study, which was built using an ontology suitable for the search domain to perform searches using the semantic web, was evaluated to have excellent results. However, it is thought that a more formalized online location is necessary to increase the accuracy and reliability of search engines and to include more comprehensive categories of search terms.