• Journal of the Korean Society for information Management
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• v.31 no.1
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• pp.99-118
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• 2014

This paper carried out co-word analysis of noun and noun phrase using text-mining technique in order to grasp the research trends on domestic and international information science articles. It was conducted based on collected titles and articles of the papers published in the Journal of the Korean Society for Information Management (KOSIM) and Journal of American Society for Information Science and Technology (JASIST) from 1990 to 2013. By dividing whole period into five publication window, this paper was organized into the following processes: 1) analysis of high frequency co-word pair to examine the overall trends of both information science articles 2) analysis of each word appearing with high frequency keyword to grasp the detailed subject 3) focused network analysis of trend after 2010 when distinctively new keyword appeared. The result of the analysis shows that KOSIM has considerable portion of studies conducted regarding topics such as library, information service, information user and information organization. Whereas, JASIST has focused on studies regarding information retrieval, information user, web information, and bibliometrics.

• Journal of Environmental Impact Assessment
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• v.26 no.5
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• pp.303-314
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• 2017

The purpose of this study was to determine domestic and foreign ecological asset research trends. We aimed to understand ecological assets research directions and trends by comprehensively analyzing 12 keywords, including those similar to keywords for comparable assets, to identify related fields and regions. Extensive analysis of domestic and foreign studies was conducted through keyword network analysis of textural information. This approach is helpful for understanding the flow of information and identifying research directions. Foreign studies based on sustainability were connected with 'Economic assessment', 'Management' and 'Policy' areas. It was difficult to determine domestic research trends because there are fewer domestic studies than foreign. There were studies that sought to identify economic value of developing regions. This research can be used to guide the research direction for future ecosystem asset analysis in Korea.

• Journal of the Korea Convergence Society
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• v.8 no.8
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• pp.71-75
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• 2017

Due to the spread of SNS, web-based consumer-generated data is increasing exponentially. It is important in many fields to accurately extract what is appropriate for the user's interest in a large amount of data. It is especially important for business mangers to establish marketing policies to find the right customers for them in many users. In this paper, we try to obtain important information centering on customers who are interested in each account through Twitter follow - following relationship. Because Twitter's current follower relationships do not reflect the user's interests, we try to figure out the details of interest using keyword extraction methods for tweets of followers. To do this, we select two domestic commercial Twitter accounts and apply the sequential pattern evaluation index to the mining key phrase of the text data collected from the follower.

• Journal of KIISE:Software and Applications
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• v.27 no.3
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• pp.248-256
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• 2000

This paper presents a personalized web agent that constructs user profile which consists of user preferences on the web and recommends his/her relevant information to the user. The personalized web agent consists of monitor agent, user profile construction agent, and user profile refinement agent. The monitor agent makes a user describe his/her preferences directly and it creates the database of preference document, finally performs several keyword extraction to increase the accuracy of the DB. The user profile construction agent transforms the extracted keywords into user profile that could be confirmed and edited by the user. and the refinement agent refines user profile by recursively learning and processing user feedback. In this paper, we describe the several keyword weighting and inductive learning techniques in detail. Finally, we describe the adaptive web retrieval and push agent that perform adaptive services to the user.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.389-397
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• 2017

Recently semantic web document is produced and added in repository in a cloud computing environment and requires an intelligent semantic agent for analytical classification of documents and information retrieval. The traditional methods of information retrieval uses keyword for query and delivers a document list returned by the search. Users carry a heavy workload for examination of contents because a former method of the information retrieval don't provide a lot of semantic similarity information. To solve these problems, we suggest a key word frequency and concept matching based semantic clustering model using hadoop and NoSQL to improve classification accuracy of the similarity. Implementation of our suggested technique in a cloud computing environment offers the ability to classify and discover similar document with improved accuracy of the classification. This suggested model is expected to be use in the semantic web retrieval system construction that can make it more flexible in retrieving proper document.

• The Journal of Society for e-Business Studies
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• v.13 no.2
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• pp.213-223
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• 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 the Korean Society for information Management
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• v.8 no.1
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• pp.78-99
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• 1991

So far, most of Korea's newspapers indexing have been done manually using tesaurus. In recent years, however, the need for automatic indexing system has grown stronger so as for indexers to save time, efforts and money. And some newspapers have started establishing their databases along with introducing electronic newspapers and CTS. This thesis is on establishing and automatic indexing system for the full-text of the Korea Economic Daily's articles, which have been accumulated in its database, KETEL. In my thesis, I suggest methods to create a keyword file, a stopword list, an auxiliary word list and an infected word list by applying linguistic analysis methods to Hangul, taking advantage of the language's morphological peculiarity. Through these studies, I was able to reach four conclusions as follows. First, we can obtain satisfactory keywords by automatic indexing methods that were made through morphological analysis. Second, an indexer can improve the efficiency of indexing work by controlling extracted vocabulary, as syntax analysis and semantic analysis is not complete in Hangul. Third, The keyword file in this system which is made of about 20,000 most-frequently-used newspaper terms can be used in the future in compiling a thesaurus. Finally, the suggested methods to prepare an auxiliary word list and an infected word list can be applicable to designing other automatic systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.432-441
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• 2002

Though many services offer useful information on internet, computer users are not so familiar with such services that they need an assistant system to use the services easily In the case of web sites, for example, the operators answer the users e-mail questions, but the increasing number of users makes it hard to answer the questions efficiently. In this paper, we propose an assistant system which responds to the users questions automatically and helps them browse the Hanmail Net FAQ (Frequently Asked Question) conceptually. This system uses two-level self-organizing map (SOM): the keyword clustering SOM and document classification SOM. The keyword clustering SOM reduces a variable length question to a normalized vector and the document classification SOM classifies the question into an answer class. Experiments on the 2,206 e-mail question data collected for a month from the Hanmail net show that this system is able to find the correct answers with the recognition rate of 95% and also the browsing based on the map is conceptual and efficient.

• Journal of Korean Medicine Rehabilitation
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• v.25 no.1
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• pp.63-70
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• 2015

Objectives The purpose of this study is to understand the research trend of reports on forest therapy so far and analyze the Korean medicine therapy being applied in forest therapy programs. Methods We ran a keyword search on domestic databases with the following keyword 'forest therapy, forest healing, forest treatment, recreational forest, forest bath, forest experience'. The search took place in December 2014 and there was no limit to search time. A total of 334 forest therapy articles have been selected. Results The number of research on forest therapy continued to rise from 1985, with 334 articles being published from 84 journals. When those 188 articles were sorted by their contents and methods, except 146 articles of survey on simple satisfaction, recognition and visting, 94 were clinical studies, 79 were literature studies, 15 were experimental studies. Of the 94 clinical researches, there were 52 CCTs (Controled Clinical Trials), 39 ODs (efficacy studies with either a controlled or an Other than controlled Design) and 3 RCTs (Randomized Clinical Trials). Among the clinical researches, there were a total of 21 studies that used Korean Medicine programs, and meditation was the most popular, being used in 18 studies. Herbal food and tea therapy and Qigong were used in 3 studies each, and Korean medicine music programs were used in 2 studies. Conclusions A systematic and standardized Korean medicine forest therapy program must be developed, and based on the program, more research treating diseases should be conducted.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.2
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• pp.205-212
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• 2013

The previous chatting systems have generally used methods based on lexical agreement between users' input sentences and target sentences in a database. However, these methods often raise well-known lexical disagreement problems. To resolve some of lexical disagreement problems, we propose a three-step sentence searching method that is sequentially applied when the previous step is failed. The first step is to compare common keyword sequences between users' inputs and target sentences in the lexical level. The second step is to compare sentence types and semantic markers between users' input and target sentences in the semantic level. The last step is to match users's inputs against predefined lexico-syntactic patterns. In the experiments, the proposed method showed better response precision and user satisfaction rate than simple keyword matching methods.