• The Journal of Society for e-Business Studies
• /
• v.13 no.2
• /
• pp.213-223
• /
• 2008

The efficient discovery of services from a large scale collection of services has become an important issue[7, 24]. We studied a syntactic method for Web service discovery, rather than a semantic method. We regarded a service discovery as a retrieval problem on the proprietary XML formats, which were service descriptions in a registry DB. We modeled services and queries as probabilistic values and devised similarity-based retrieval techniques. The benefits of our way are follows. First, our system supports ranked service retrieval by keyword search. Second, we considers both of UDDI data and WSDL definitions of services amid query evaluation time. Last, our technique can be easily implemented on the off-theshelf DBMS and also utilize good features of DBMS maintenance.

• Journal of Internet Computing and Services
• /
• v.7 no.2
• /
• pp.71-80
• /
• 2006

In web search engines, there are two main methods: directory searching and keyword searching. Keyword searching shows high recall rate but tends to come up with too many search results to find which users want to see the pages. Directory searching has also a difficulty to find the pages that users want in case of selecting improper category without knowing the exact category, that is, it shows high precision rates but low recall rates. We designed and implemented a new web search engine to resolve the problems of directory search method. It regards a category as a fuzzy set which contains keywords and calculate the degree of inclusion between categories. The merit of this method is to enhance the recall rate of directory searching by expanding subcategories on the basis of similarity.

• Convergence Security Journal
• /
• v.22 no.2
• /
• pp.9-19
• /
• 2022

As the expansion of digital transformation, we are more exposed to the threat of cyber attacks, and many institution or company is operating a signature-based intrusion prevention system at the forefront of the network to prevent the inflow of attacks. However, in order to provide appropriate services to the related ICT system, strict blocking rules cannot be applied, causing many false events and lowering operational efficiency. Therefore, many research projects using artificial intelligence are being performed to improve attack detection accuracy. Most researches were performed using a specific research data set which cannot be seen in real network, so it was impossible to use in the actual system. In this paper, we propose a technique for classifying major attack keywords in the security event log collected from the actual system, assigning a weight to each key keyword, and then performing a similarity check using TF-IDF to determine whether an actual attack has occurred.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2021.07a
• /
• pp.79-80
• /
• 2021

인터넷은 우리 경제를 디지털 경제로 변화시키며 전자상거래도 증가하고 있다. 따라서 구매자가 전자상거래에서 남기는 긍정적인, 부정적인 상품평은 상품기획의 주요 정보가 될 수 있다. 본 논문에서는 버티컬 무소음 마우스 10,000개에 대한 정형화된 데이터셋을 Word2Vec을 이용하여 유사도 분석, 온라인 상품평 빈도분석 상위 50개 단어를 제시하여 실제 상품을 사용한 후 설문조사 시행을 하였다. 온라인 상품평 유사도 분석결과 클릭 키워드에 대한 장점으로 통증(.986), 디자인(.982)가 분석되었으며 단점은 적응(.866), 불편(.854)이었다. 오프라인 상품평에서는 장점으로 디자인(17명), 단점으로 불편(11명)이었다. 또한 온라인과 오프라인의 상품평을 비교함으로써 구매자의 긍정, 부정의 의미를 교차 확인하여 유의미한 정보를 제시 하였다고 볼수 있다. 따라서 본 연구에서 제시하는 상품기획 프로세스를 신상품 개발 및 기존 상품의 개선 전략으로 적용할 수 있겠다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2020.07a
• /
• pp.619-623
• /
• 2020

한국어는 교착어로 1개 이상의 형태소가 단어를 이루고 있기 때문에 텍스트 분석 시 형태소를 분리하는 작업이 필요하다. 자연어를 처리하는 대부분의 알고리즘은 영미권에서 만들어졌고 영어는 굴절어로 특정 경우를 제외하고 일반적으로 하나의 형태소가 단어를 구성하는 구조이다. 그리고 영문은 주로 띄어쓰기 위주로 토큰화가 진행되기 때문에 텍스트 분석이 한국어에 비해 복잡함이 떨어지는 편이다. 이러한 이유들로 인해 한국어 텍스트 분석은 영문 텍스트 분석에 비해 한계점이 있다고 알려져 있다. 한국어 텍스트 분석의 성능 향상을 위해 본 논문에서는 번역 전처리 기법을 제안한다. 번역 전처리 기법이란 원본인 한국어 텍스트를 영문으로 번역하고 전처리를 거친 뒤 분석된 결과를 재번역하는 것이다. 본 논문에서는 한국어 뉴스 기사 데이터와 번역 전처리 기법이 적용된 영문 뉴스 텍스트 데이터를 사용했다. 그리고 주제어 역할을 하는 키워드를 단어 간의 유사도를 계산하는 알고리즘인 Word2Vec(Word to Vector)을 통해 유사 단어를 추출했다. 이렇게 도출된 유사 단어를 텍스트 분석 전문가 대상으로 성능 비교 투표를 진행했을 때, 한국어 뉴스보다 번역 전처리 기법이 적용된 영문 뉴스가 약 3배의 득표 차이로 의미있는 결과를 도출했다.

• Journal of Internet Computing and Services
• /
• v.6 no.2
• /
• pp.99-115
• /
• 2005

Extensible Markup Language (XML) is an Internet standard that is used to express and convert data, In order to find the necessary information out of XML documents, you need a search system for XML documents, In this research, we have developed a search system that can find documents that matches the structure and content of a given XML document, making the best use of XML structure, Search metrics take account of the similarity in tag names, tag values, and the structure of tags, After a search, the system displays the ranked results in the order of aggregate similarity, Three methods of query are provided: keyword search which is conventional; search with tag names and their values; and search with XML documents, These three methods enable users to choose the method that best suits their preference, resulting in the increase of the usefulness of the system.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.5
• /
• pp.640-649
• /
• 2018

This study analyzed the consumer awareness of cycling wear using web mining, one of the big data analysis methods. For this, the texts of postings and comments related to cycling wear from 2006 to 2017 at Naver cafe, 'people who commute by bicycle' were collected and analyzed using R packages. A total of 15,321 documents were used for data analysis. The keywords of cycling wear were extracted using a Korean morphological analyzer (KoNLP) and converted to TDM (Term Document Matrix) and co-occurrence matrix to calculate the frequency of the keywords. The most frequent keyword in cycling wear was 'tights', including the opinion that they feel embarrassed because they are too tight. When they purchase cycling wear, they appeared to consider 'price', 'size', and 'brand'. Recently 'low price' and 'cost effectiveness' have become more frequent since 2016 than before, which indicates that consumers tend to prefer practical products. Moreover, the findings showed that it is necessary to improve not only the design and wearability, but also the material functionality, such as sweat-absorbance and quick drying, and the function of pad. These showed similar results to previous studies using a questionnaire. Therefore, it is expected to be used as an objective indicator that can be reflected in product development by real-time analysis of the opinions and requirements of consumers using web mining.

• Spatial Information Research
• /
• v.18 no.4
• /
• pp.129-140
• /
• 2010

Large portal sites such as Google, NAVER provide Various services based on the map. Thus, interest and demand of users who want to obtain the region-related information has been increased. And services that combine the regional information with the map are provided currently at the large portal sites. However, the existing services of large portal sites do not provide enough detailed information and are inconvenient because acquisition process of related information is repeated. Therefore, the system that enables users to obtain detailed information related on the specific region synthetically and easily is needed. In this paper, we propose a system model using map interface and knowledge-processing in order to build the system that is useful for acquiring regional information. The model consists of 3-Layers: 'Regional Information Web-Documents Layer', 'Unique Regional Information Layer', and "Map-Interface Layer'. The Integrated Region~Related Information Searching System based on the model is implemented through the following 4-steps: (1) extracting the keywords that represent specific region (2) collecting the related web pages (3) extracting a set of related keywords and computing an association between the keywords (4) implementing a user interface. We verified validity on the model we proposed. knowledge-processing algorithm using affinity matrix, and UI that help users conveniently search by applying the system to region of the Goyang City. This system integrates regional information existing merely individual 'information' and provides users the 'knowledge' that is newly produced and organized. Users can obtain various detailed regional information and easily get related information through this system.

• Korean Journal of Comparative Education
• /
• v.28 no.1
• /
• pp.1-24
• /
• 2018

The objective of the article is to find the research trends and the main traits presented in the keywords on abstracts of research articles of "International Journal of Education Development" from 2002 to 2017. To do this, Text Network Analysis(TNA) was applied targeting 966 papers on the journal and the major research outcomes are as follows. First, the frequency analysis on the keywords showed that the keywords like Administration of education program, Schools and instruction, Regional public administration, Educational support service, Elementary education, and Elementary and secondary school were analyzed more than 100 times and also high in centrality degree. Second, the analysis results of the keywords presented in those research articles by development goal periods showed that several new keywords like Elementary education, Elementary and secondary school, Education quality, Secondary education, Educational planning have emerged frequently after SDGs and these keywords showed high in their centrality analysis. Third, the analysis on education level showed that the keywords like Elementary education, Administration of education program, School children were high in frequency and centrality degree in Elementary level. In secondary level, Schools and instruction, Administration of education program, Academic achievement were high, and in high level, college and university was high, respectively.

• 한국체육학회지인문사회과학편
• /
• v.55 no.6
• /
• pp.801-810
• /
• 2016

The purpose of the study was to conduct a text mining examining keywords related to the National Paralympics and provide the fundamental information that would be used to change perception of people without disabilities toward disabilities and to promote the social participation of people with and without disabilities in the National Paralympics. Social big data regarding the National Paralympics were retrieved from news articles and blog postings identified by search engines, Naver, Daum, and Google. The data were then analysed using R-3.3.1 Version Program. The analysing techniques were cloud analysis, correlation analysis and social network analysis. The results were as follows. First, news were mainly related to game results, sports events, team participation and host avenue of the 33rd ~ 36th National Paralympics. Second, search results about the 33rd ~ 36th National Paralympics between Naver, Daum, and Google were similar to one another. Thirds, the keywrods, National Paralympics, sports for the disabled, and sports, demonstrated a high close centrality. Further, degree centrality and betweenness centrality were associated in the keywords such as sports for all, participation, research, development, sports-disabled, research-disabled, sports for all-participation, disabled-participation, sports for all-disabled, and host-paralympics.