• Korean Journal of Human Ecology
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• v.21 no.6
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• pp.1129-1144
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• 2012

The purpose of this study was to investigate the gender difference in adolescent's problem behavior and depression, and The main aim of this study was to develop a fundamental web design to provide information content that would be easy for average consumers to understand based on the classification of information related to food safety. Based on the information obtained through in-depth interviews, the researchers developed an information classification system that meets the needs of consumers, and which serve as a basic framework for a homepage for a food safety information center. A total of 62 food items in 6 areas were selected based on reports of food safety related events occurring between 1998-2009 (KFDA 2008). The classification system of risk factors such as chemical risk factors and biological risk factors were categorized. The specific features of the information content for individual food items provided for classification based on evaluation by professional food scientists and the importance of risk factors. By providing a consumer participation section and company participation section, it was anticipated that the food safety information center would be able to act as a moderator for food safety information communication among consumers, the food industry, and the government. Based on the development of a classification system and framework, a design plan and tree-map for the internet site was developed.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.185-192
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• 2013

In this paper, proposed to improve the performance of speech and mixed content signal classification using MFCC based on GMM probability model used for the MPEG USAC(Unified Speech and Audio Coding) standard. For effective pattern recognition, the Gaussian mixture model (GMM) probability model is used. For the optimal GMM parameter extraction, we use the expectation maximization (EM) algorithm. The proposed classification algorithm is divided into two significant parts. The first one extracts the optimal parameters for the GMM. The second distinguishes between speech and mixed content signals using MFCC feature parameters. The performance of the proposed classification algorithm shows better results compared to the conventionally implemented USAC scheme.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.650-660
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• 2017

This study is to suggest a new method of analyzing personality types of characters in narrative. First, we examined the history of the taxonomy of character types that existed in narrative theories so far. Until now, the classification of character types in narrative theory consisted largely of a formal classification based on roles in narrative, a content classification based on human internal qualities, and a complementary classification in which the two classification criteria are united. The problem with the existing character classification type is difficult to categorize it in spite of the usefulness of the content classification based on human internal qualities. On the other hand, the classification based on the role of the character in the narrative does not help as much as a practical analysis methodology because the classification is formal. In this study, we try to solve this problem by introducing Shalom Schwartz's human value type, and to make human character's value type and human role correlated with each other as a new character analysis methodology. Schwartz's study of value type is a very effective method to grasp the motivation of human behavior, and it seems to be very meaningful in analyzing the directivity of characters.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.224-231
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• 2013

Defining the concept of prominent audio content as the most informative audio content from the users' perspective within a given unstructured audio segment, we propose a simple but robust intensity-based attack/release pattern features to detect the prominent audio content. We also propose a web-based annotation procedure to retrieve users' subjective perception and annotated 18 hours of video clips across various genres, such as cartoon, movie, news, etc. The experiments with a linear classification method whose models are trained for speech, music, and sound effect demonstrate promising - but varying across the genres of programs - results (e.g., 86.7% weighted accuracy for speech-oriented talk shows and 49.3% weighted accuracy for {action movies}).

• Journal of Korean Academy of Nursing
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• v.17 no.1
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• pp.9-23
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• 1987

Nursing service, as the largest user of labor resources, has become concerned about appropriate allocation of staffing resources. Therefore, this project was designed to measure quantitatively the direct nursing care provided to patients and to develop a new patient classification system based on the direct nursing care activities. The initial step in the development of the classification instrument was to identify the content of direct nursing activities. The frequency with which these activities were carried out, the total time spent in carrying them out and the average time for one performance of each of the nursing activities was calculated. The next step was to select the items for the classification instrument taking into account these direct nursing activities. A list of 40 items was prepared. These items were then classified into 8 major categories: personal hygiene, moving ＆ exercise, nutrition & elimination, observation, medication, treatment, collecting specimens and other care activities for severity ill patients. Each item was assigned a value unit based on the average time required by the nursing staff to complete the specific item. The third step was to determine the practicality of the items and value units, so an attempt was made to establish content validity for these items and units by obtaing a consensus from 8 head nurses, representing eight different departments. The 4th step was to conducted a pilot study to establish the score range for the classification boundaries. For this purpose an instrument was designed using the list of items and value units and a prepared classification criteria as a guideline to validate the patient classification. A judgment group consisting of 52 supervisory nurses and head nurses were asked to select the proper patient to fit each classification criteria and to fill out the instrument for each patient. The total value unit and the frequency for each classification group was calculated. According to the frequency distribution, the score range for the classification group was determined as follows : 0~15 for groupI, 16~30 for group II, 31~50 for group III, and above 51 for group IV. Finally a patient classification form was developed.

• Journal of Information Science Theory and Practice
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• v.1 no.1
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• pp.10-26
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• 2013

Domain transfer is a widely recognized problem for machine learning algorithms because models built upon one data domain generally do not perform well in another data domain. This is especially a challenge for tasks such as opinion classification, which often has to deal with insufficient quantities of labeled data. This study investigates the feasibility of self-training in dealing with the domain transfer problem in opinion classification via leveraging labeled data in non-target data domain(s) and unlabeled data in the target-domain. Specifically, self-training is evaluated for effectiveness in sparse data situations and feasibility for domain adaptation in opinion classification. Three types of Web content are tested: edited news articles, semi-structured movie reviews, and the informal and unstructured content of the blogosphere. Findings of this study suggest that, when there are limited labeled data, self-training is a promising approach for opinion classification, although the contributions vary across data domains. Significant improvement was demonstrated for the most challenging data domain-the blogosphere-when a domain transfer-based self-training strategy was implemented.

• Journal of the Korean Society for Library and Information Science
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• v.33 no.1
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• pp.87-111
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• 1999

This article investigates the functions, needs, and developments of the MARC format for classification data. and recommends the development for the KORMARC format for classification data. It ae analyzes the record structure, content designation and the content of it mainly based on USMARC format. Structure and content designation are almost same with those of the bibliographic and authority formats. The data fields divided into functional blocks based on their functions. Record contents of the data in the fixed-length fields include more elements on the classification numbers, including type of number, classification validity, standard or optional number, synthesized number. Variable fields can be grouped into several blocks, inducing those for numbers and codes: for classification numbers and terms; for references and tracings; for notes fields: for index terms fields, and for number building fields. Data in each fields of this format have the same contents with those in other related fields as soon as possible. This article analyzes the content in each data fields in detail.

• MALSORI
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• v.68
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• pp.75-93
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• 2008

An example-based dialogue system tries to utilize many pairs which are stored in a dialogue database. The most important part of the example-based dialogue system is to find the most similar utterance to user's input utterance. Modality, which is characterized as conveying the speaker's involvement in the propositional content of a given utterance, is one of the core sentence features. For example, the sentence "I want to go to school." has a modality of hope. In this paper, we have proposed a modality classification system which can predict sentence modality in order to improve the performance of example-based dialogue systems. We also define a modality tag set for a dialogue system, and validate this tag set using a rule-based modality classification system. Experimental results show that our modality tag set and modality classification system improve the performance of an example-based dialogue system.

• Journal of the Korean Society for information Management
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• v.31 no.3
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• pp.313-329
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• 2014

This study aims to provide intellectual access to TV content using faceted classification. In order to describe the content of news and current affairs programs, a faceted approach was explored. Based on the Ranganathan's PMEST formula, the basic facets - 'who', 'what', 'how', 'where', 'when' - and their sub-facets were created, specifically for describing the news genre. Additionally, the formal structure and the contextual features of the news genre were mainly considered for creating sub-facets. These created facets were applied to a news genre program. The result shows that these suggested facets are useful for representing well the contextual components of the news genre. The application of faceted classification is expected to improve the identification of the specific TV content.

• Journal of Korean Academy of Nursing Administration
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• v.13 no.1
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• pp.5-16
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• 2007

Purpose: This study is to verify the validity and reliability of classified items and criteria of the patient classification system(PCS) based on Park's definition of nursing intensity. Methods: An expert group of 8 persons verified the content validity of the tools. The 1817 inpatients at a tertiary hospital in Seoul, Korea were classified into 4 groups according to two tools for verifying concurrent validity and interraters' reliability. These verifications were performed from September to October, 2004. Results: Nursing domains of the tools have been divided into 12 items: hygiene, nutrition, elimination, exercise & activity, education & counseling, emotional support, communication & consciousness, treatment & examination, medication, measurement & observation, coordination of multidisciplinary team, admission & discharge & transfer management. Content validity was verified by the content validity index(above 0.75 in all 12 areas). Interraters' reliability was no significant difference in the results of the patient classification between the two raters(A group 93.75%. B group 88.24%). Concurrent validity was also verified by the agreement of two tools(73.7%). Conclusion: These results showed that the reliability and validity of the PCS based on the nursing intensity were verified. These will use an data for nursing productivity in the future.