• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.6 no.5
• /
• pp.409-419
• /
• 2016

In general, Area studies have very flexible field of research, so it is very difficult to proceed all field of research at the same time. Due to this, researches on Area studies have been changed the field of research and research trends according to age. So it is important to identify research trends for performing Area studies. Also, interests for understanding the research trend of Area studies are increasing constantly. In this paper, we analyze research trends of Mediterranean Area studies in Korea by using co-appearance keywords. To do this, we first analyze article types and extract co-appearance keywords on articles of 『Journal of Mediterranean Area Studies』, which is the representative journal of Mediterranean region in Korea. In details, trends analysis of Mediterranean Area studies would be performed by using cp-keywords of article and visualizing network graph forms.

• The KIPS Transactions:PartB
• /
• v.10B no.1
• /
• pp.41-46
• /
• 2003

This thesis composes separated words in text for extracting keywords from Japanese, proposes extracting indexing keywords which consist of a compound noun using words and sentences information with the rules in the sentences. It constructs generative rules of compound nouns to be based In dependence as a result of analysing character of keywords in the text not the same way as before. To hold other extracting keywords and the content of sentence, and suggest how to decide importance concerned some restriction and repetition of words about generative rules. To verify the validity of keywords extracting, we have used titles and abstracts from Japanese thesis 65 files about natural language and/or voice processing, and obtain 63% in outputting one in the top rank.

• The Journal of the Korea Contents Association
• /
• v.20 no.12
• /
• pp.23-35
• /
• 2020

This study aims to examine trends in the IoT field by collecting and analyzing domestic papers on IoT that will have a great impact across industries and society. The survey period for this study was from 2015 to 2019, and the domestic papers on the IoT were collected using Naver's Academic Information. We extracted the keywords with high frequency from the domestic papers collected by the period and performed the centrality analysis to identify the central keywords among the keywords with high frequency. In terms of keyword frequency, 'sensor' and 'security' from 2015 to 2017 appeared as the top keywords with high frequency. From 2017, 'car' and 'intelligence' appeared as the top keywords with high frequency. In terms of keyword centrality, 'security' and 'sensor' from 2015 to 2016 appeared as highly centralized keywords. From 2017, 'intelligence', 'car' and 'industrial revolution' appeared as highly centralized keywords.

• Journal of Satellite, Information and Communications
• /
• v.7 no.3
• /
• pp.86-93
• /
• 2012

In this paper, we propose keyword search and ranking methods for OWL documents that describe metadata and ontology on the Semantic Web. The proposed keyword search method defines a unit of keyword search result as an information resource and expands a scope of query keyword to names of class and property or literal data. And we reflected derived information by inference in the keyword search by considering the elements of OWL documents such as hierarchical relationship of classes or properties and equal relationship of classes. In addition, our method can search a large number of information resources that are relevant to query keywords because of information resources indirectly associated with query keywords through semantic relationship. Our ranking method can improve user's search satisfaction because of involving a variety of factors in the ranking by considering the characteristics of OWL. The proposed methods can be used to retrieve digital contents, such as broadcast programs.

• Journal of Elementary Mathematics Education in Korea
• /
• v.23 no.4
• /
• pp.459-479
• /
• 2019

The purpose of this study is to explore the research trends and knowledge structures of 『Journal of Elementary Mathematics Education in Korea』 by applying the keyword network analysis. To do this, we analyzed the frequency of the occurrence of keywords in the journal and conducted keyword network analysis using the Krkwic program and NodeXL program. The results of the analysis are as follows. Firstly, 749 keywords were extracted from keyword cleansing process and 48 keywords, including mathematics curriculum, mathematics textbooks, school mathematics, mathematical problem solving, mathematically gifted student, etc. appeared more than five times. Secondly, the keyword network analysis showed that the keywords-mathematics textbooks, school mathematics, mathematical problem solving, mathematical communications-have high connection centrality. Finally, we provided the limitations of this study and suggested future research.

• Proceedings of the KAIS Fall Conference
• /
• 2008.11a
• /
• pp.32-35
• /
• 2008

본 논문은 포털 사이트의 효율적인 광고 제공을 위한 자연어처리 기반의 키워드 광고 시스템을 제안한다. 사용자의 질의에 대한 형태소 분석 결과를 사용하여, 기존의 키워드 정합에 의한 광고 시스템보다 재현율을 향상시킬 수 있었다. 또한, 웹 기반 키워드 광고 뿐 아니라 메신저를 통한 대화 내용 기반 키워드 광고도 제안한다.

• Journal of Internet Computing and Services
• /
• v.16 no.3
• /
• pp.43-57
• /
• 2015

In this thesis was conducted to propose a method for efficient information retrieval using concept lattices. Since this thesis designed a new system based on ordinary concept lattices, it has the same approach method as ontology, but this thesis proposes new concept lattices to be used by establishing collaborative relations between objects and concepts that users are likely to search information more efficiently. The system suggested by this thesis can be summarized as below. Firstly, this system leads to a collaborative search by using Three kinds of concepts, such as keyword concept lattices, which focus on input key words, expert concept lattices recommended by experts and theme concept lattices, and based on these 3 concept lattices, it will help users search information they want more efficiently. Besides, as the expert concept and the keyword concept become combined, further providing users with the frequency of keyword and the frequency of category, this system can function to recommend key words related to search words entered by users. Another function of this system is to inform users of key words and categories used in users' interested themes by using the theme concept lattices. Secondly, when there is not keyword entered by a user, it is possible for users to achieve the goal of search through the secondary search when this system provides them with key words related to the input keyword. Thirdly, since most of the information is managed while being dispersed, such dispersed and managed information not only has different expression methods but changes as time goes. Accordingly, By using XMDR for efficient data access and integration of distributed information, this thesis proposes a new technique and retrieval system to integrate dispersed data.

• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.3
• /
• pp.187-194
• /
• 2013

Recently, there have been many trials to analyze characteristics of research trends through a structural analysis of keyword networks in various fields. However, most previous studies have mainly focused on structural analysis harbored in some static networks and there is a lack of research on changes of such networks structure with time. In this paper, we constructed annual keyword networks by using a database of papers published in the international computer engineering-field journals from 2002 through 2011, and examined the changes of them. As a result, it was shown that most keywords in a network are preserved in the network of the next year, and their degree of connectivity and the average weight of the connections were higher and smaller, respectively, than those of the keywords which are not preserved. In addition, when a keyword network shifted to one of the next year, the connections between keywords were more likely to be removed than preserved, and the average weight of the removal connections was higher than that of the preserved ones. These results imply that the keywords are not changed over time but their connections are very likely to be changed; and there is apparent differences between the preserved and removal groups of keywords/connections with respect to degree and weights of connections. All these results are consistently observed over the ten-year datasets and they can be important principles in understanding the structural changes of the keyword networks.

• Annual Conference on Human and Language Technology
• /
• 2015.10a
• /
• pp.213-215
• /
• 2015

국립국어원 온라인가나다에서 제공되는 질의응답 문서를 이용한 국어정보에 대한 Q&A시스템은 언어 자체에 대한 질문과 답변의 특성으로 조사나 어미로 끝나는 표현이 주어로 등장하는 등의 특이한 문장이 자주 나타난다. 이러한 이유로 형태소 분석을 거쳐 명사를 키워드로 추출하는 일반적인 키워드 추출 방식은 좋은 성능을 얻기 어렵다. 본 논문에서는 국어정보 질의응답 문서의 특징에 맞는 키워드 추출 방법을 제안한다. 제안하는 방식에서는 문장 단위로 분할된 결과에서 연결어미로 문장을 추가로 분할한 뒤에 조사 앞에 나타나는 단어열을 키워드로 추출한다. 덧붙여 다자비교형 질의에서의 키워드 추출을 위해 편집거리를 이용한 키워드 추출 방법을 제안한다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.14 no.6
• /
• pp.1403-1408
• /
• 2010

Korean information retrieval uses noun as index terms or keywords of representing the document. and noun and keyword extraction is to find all nouns presented in the document, In this paper, we proposes the method of keyword extraction using pre-built dictionary. This method reduces the execution time by reducing unnecessary operations. And noun, even large documents without affecting significantly the accuracy, can be extracted. This paper proposed noun extraction method using the appearance characteristics of the noun and keyword extraction method using unsupervised learning techniques.