• Journal of the Korean Dietetic Association
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• v.7 no.3
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• pp.282-294
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• 2001

n accordance with the National Health Promotion Act of 1995, newly designed National Health and Nutrition Survey was carried out in winter of 1998. Although this survey amended most of the problems noted in previous Nutrition Surveys, it still had a limitation in reflecting seasonal variation in food intake due to the survey period which was confined to November and December. In order to counterbalance this limitation and estimate the yearly food intake of Korean population, three seasonal nutrition surveys were taken place in spring, summer, and fall of 1999. Seasonal Nutritional survey targeted 15 households each in 60 nationwide primary sampling units(PSUS) which were part of 200 PSUS of 1998 National Health and Nutrition Survey. Therefore, total of 2,700 households were surveyed in 3 seasons. The interviewers visited each household members and carried out face to face interview on household. Daily food intake was monitored using 24 hour recall method. According to the survey results, fruits, beverage and alcohol intake showed large variation with season while processed foods showed almost no variation. And intake of vegetables and fruits were influenced by their own harvesting time and had impact on the list of foods consumed most. With the result of the 1998 NHNS, this study made it possible to estimate the yearly average food intake of Korean population. The result of this survey is expected to be used in planning food supply and setting tolerance level of contaminants of each foods at the government level.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.17-21
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• 2000

Typical image features such as color, shape, and texture are used in content based image retrieved. Retrieval which uses only one image feature has little performance in case that the content of image is complex or database contains many images. So, many approaches for integrating these features have been studied. However, the problem of these approaches is how to appropriately weight the image features at query time. In this paper, we propose a new retrieval method using automatically weighted image features. We perform computer simulations in test database which consists of various kinds of images. The experimental results show that the proposed method has better performance than previous works, which use fixed weight for each feature mostly, in respect to several performance cvaluations such as precision vs recall, retrieval efficiency, and ranking measure.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.10-20
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• 2010

This paper presents chunking strategy of a contiguous nouns sequence using semantic class. We call contiguous nouns which can be treated like a noun the compound noun phrase. We use noun pairs extracted from a syntactic tagged corpus and their semantic class pairs for chunking of the compound noun phrase. For reliability, these noun pairs and semantic classes are built from a syntactic tagged corpus and detailed dictionary in the Sejong corpus. The compound noun phrase of arbitrary length can also be chunked by these information. The 38,940 pairs of 'left noun - right noun', 65,629 pairs of 'left noun - semantic class of right noun', 46,094 pairs of 'semantic class of left noun - right noun', and 45,243 pairs of 'semantic class of left noun - semantic class of right noun' are used for compound noun phrase chunking. The test data are untrained 1,000 sentences with contiguous nouns of length more than 2randomly selected from Sejong morphological tagged corpus. Our experimental result is 86.89% precision, 80.48% recall, and 83.56% f-measure.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.1-10
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• 2006

In document clustering methods, the k-means algorithm and the Hierarchical Alglomerative Clustering(HAC) are often used. The k-means algorithm has the advantage of a processing time and HAC has also the advantage of a precision of classification. But both methods have mutual drawbacks, a slow processing time and a low quality of classification for the k-means algorithm and the HAC, respectively. Also both methods have the serious problem which is to compute a document similarity whenever new document is inserted into a cluster. A main property of web resource is to accumulate an information by adding new documents frequently. Therefore, we propose a new method of transitive closure tree based on the HAC method which can improve a processing time for a document clustering, and also propose a superior incremental clustering method for an insertion of a new document and a deletion of a document contained in a cluster. The proposed method is compared with those existing algorithms on the basis of a pre챠sion, a recall, a F-Measure, and a processing time and we present the experimental results.

• Nutrition Research and Practice
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• v.6 no.3
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• pp.254-262
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• 2012

The objective of this study was to provide information regarding trends of rice consumption of Korean adults based on different meal types. Respondent reports 24-hour recall data from the Korean National Health and Nutrition Examination Survey were used to assess daily rice consumption and intake ratios of rice for different meal types and places of preparation. Rice intake had gradually decreased from 224.6 g in 1998 to 190 g in 2001 and to 179.4 g in 2005. The rice consumption of Korean adults decreased every year in all ages for all places of meal preparation in 2001 and 2005 compare to 1998. Analysis for each meal type showed that rice intake at breakfast had not considerably changed, but rice intake had decreased at lunch and dinner. While the rice consumption ratio at lunch and dinner decreased, it also decreased or did not change at snack times except for the 19-29 age groups. All the age groups revealed comparable change in the analysis for meal types. There was some diversity between all age divisions in daily rice intake depending on place of meal preparation. The rice consumption by place of meal preparation was generally highest at home, lowest at other places, but it decreased in all places. The rice consumption at home was highest in the over 50 age group, lowest in the 20-30 age group. These changes seem to be related to food intake patterns of rice and substitutional foods in the diets and development regarding socio-economic status. So the need for further study on differences in rice intake based on socioeconomic levels and age group are indicated.

• Nutrition Research and Practice
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• v.6 no.4
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• pp.349-356
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• 2012

Several studies have been conducted on dietary patterns based on carbohydrate nutrition in Asian populations. We examined the cross-sectional associations in dietary patterns based on carbohydrate nutrition, including the glycemic index (GI) with dyslipidemia and diabetes among the Korean adult population. We analyzed 9,725 subjects (3,795 men and 5,930 women, ${\geq}$ 20 years) from the Fourth Korea National Health and Nutrition Examination Survey. Dietary information was collected using single 24-hour recall. Reduced rank regression was used to derive dietary patterns from 22 food groups as predictor variables and four dietary factors related to the quantity and quality of carbohydrates as response variables. Two dietary patterns were identified: 1) the balanced pattern was characterized by high intake of various kinds of foods including white rice, and 2) the rice-oriented pattern was characterized by a high intake of white rice but low intake of vegetables, fruits, meat, and dairy products. Both patterns had considerable amounts of total carbohydrate, but GI values differed. The rice-oriented pattern was positively associated with hypertriglyceridemia in men and low high density lipoprotein-cholesterol in both men and women. The balanced pattern had no overall significant association with the prevalence of dyslipidemia or diabetes, however, men with energy intake above the median showed a reduced prevalence of diabetes across quintiles of balanced pattern scores. The results show that dietary patterns based on carbohydrate nutrition are associated with prevalence of dyslipidemia and diabetes in the Korean adult population.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1237-1246
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• 1999

최근 모든 분야에서 외국과의 교류가 증대됨에 따라서 한국어 문서에는 점점 더 많은 외국어 음차 표기가 사용되는 경향이 있다. 하지만 같은 외국어에 대한 음차 표기에 개인차가 심하여 이들 음차 표기를 포함한 문서들에 대한 검색을 어렵게 만드는 원인이 되고 있다. 한 가지 해결 방법은 색인 시에 같은 외국어에서 온 음차 표기들을 등가부류로 묶어서 색인해 놓았다가 질의 시에 확장하는 방법이다. 본 논문에서는 외국어 음차 표기들의 등가부류를 만드는데 필요한 음차 표기의 음성적 유사도 비교 알고리즘인 Kodex를 제안한다. Kodex 방법은 기존의 스트링 비교 방법인 비음성적 방법에 비해 음차 표기들을 등가부류로 클러스터링하는데 있어 더 나은 성능을 보이면서도, 계산이 간단하여 훨씬 효율적으로 구현될 수 있는 장점이 있다.Abstract With the advent of digital communication technologies, as Koreans communicate with foreigners more frequently, more foreign word transliterations are being used in Korean documents more than ever before. The transliterations of foreign words are very various among individuals. This makes text retrieval tasks about these documents very difficult. In this paper we propose a new method, called Kodex, of measuring the phonetic similarity among foreign word transliterations. Kodex can be used to generate the equivalence classes of the transliterations while indexing and conflate the equivalent transliterations at the querying stage. We show that Kodex gives higher precision at the similar recall level and is more efficient in computation than non-phonetic methods based on string similarity measure.

• Journal of KIISE
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• v.42 no.4
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• pp.512-521
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• 2015

Internet users purchase goods on the Internet and express their positive or negative emotions of the goods in product reviews. Analysis of the product reviews become critical data to both potential consumers and to the decision making of enterprises. Therefore, the importance of opinion mining techniques which derive opinions by analyzing meaningful data from large numbers of Internet reviews. Existing studies were mostly based on comments written in English, yet analysis in Korean has not actively been done. Unlike English, Korean has characteristics of complex adjectives and suffixes. Existing studies did not consider the characteristics of the Internet language. This study proposes an emotional classification method which increases the accuracy of emotional classification by analyzing the characteristics of the Internet language connoting feelings. We can classify positive and negative comments about products automatically using the Internet emoticon. Also we can check the validity of the proposed algorithm through the result of high precision, recall and coverage for the evaluation of this method.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.7
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• pp.283-290
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• 2015

In this paper, we propose a hybrid method for the recognition of answer types in the WiseQA system. The answer types are classified into two categories: the lexical answer type (LAT) and the semantic answer type (SAT). This paper proposes two models for the LAT detection. One is a rule-based model using question focuses. The other is a machine learning model based on sequence labeling. We also propose two models for the SAT classification. They are a machine learning model based on multiclass classification and a filtering-rule model based on the lexical answer type. The performance of the LAT detection and the SAT classification shows F1-score of 82.47% and precision of 77.13%, respectively. Compared with IBM Watson for the performance of the LAT, the precision is 1.0% lower and the recall is 7.4% higher.

• Journal of KIISE:Databases
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• v.35 no.4
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• pp.345-355
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• 2008

SIFT is popularly used in computer vision application such as object recognition, motion tracking, and 3D reconstruction among various shape descriptors. However, it is not easy to apply SIFT into the image similarity search as it is since it uses many high dimensional keypoint vectors. In this paper, we present a SIFT based image similarity search method using an edge image pyramid and an interesting region detection. The proposed method extracts keypoints, which is invariant to contrast, scale, and rotation of image, by using the edge image pyramid and removes many unnecessary keypoints from the image by using the hough transform. The proposed hough transform can detect objects of ellipse type so that it can be used to find interesting regions. Experimental results demonstrate that the retrieval performance of the proposed method is about 20% better than that of traditional SIFT in average recall.