• Culinary science and hospitality research
• /
• v.21 no.3
• /
• pp.181-197
• /
• 2015

This study examined the influence of perceived value, perceived quality, reasonable price of subtropical vegetables on trust, purchase intention and word of mouth among hotel chefs. For this investigation, a survey was carried out targeting hotel chefs in Korea with experience with subtropical vegetables. A total of 380 questionnaires were distributed to selected chefs over 20 days from October 1st to October 20th, 2014, of which 353 valid questionnaires were used after the exclusion of responses missing values or too much weighted tendency. A frequency analysis, factor analysis, correlation analysis, and multiple regression analysis were conducted with the use of the SPSS 18.0 package. The analysis results are as follows. First, perceived value, perceived quality and reasonable price had a positive influence on trust. Second, trust had a positive effect on purchase intention and word of mouth. Third, purchase intention positively influenced word of mouth.

• Korean Journal of Child Studies
• /
• v.37 no.4
• /
• pp.159-168
• /
• 2016

Objective: This study investigated the age at which monolingual children can understand that different languages are different conventional systems of communication. In particular, we investigated when children can suspend using the mutual exclusivity (ME) assumption that a label solely refers to one category when interpreting novel words from foreign languages. Methods: Two-year-olds (n = 16) and 3-year-olds (n = 16) participated in the procedure, which consisted of three blocks. In the first block, a Korean speaker taught the children a novel word, muppi, referring to a novel object. The children were presented with two objects, muppi and another novel object. The Korean speaker then asked the children to find a referent of either muppi or the other novel Korean label, kkati. In the second block, a foreign language (either English or Spanish) speaker asked children to find the object for a foreign novel word, sefo, presenting two objects: muppi and the third novel object, which had not been presented before. The procedure of the third block was identical to that of the first block. Results: Three-year-olds exploited the ME assumption when interpreting a Korean novel word but not when interpreting a foreign novel word. In contrast, 2-year-old children did not use the ME assumption when interpreting native and foreign words. Conclusion: Children acquire an understanding that native and foreign languages have different words for an object at least by 3 years of age.

• Journal of the Korean School Mathematics Society
• /
• v.13 no.3
• /
• pp.381-395
• /
• 2010

The purpose of this paper is to examine the competence and the methods of problem solving in four operations word problems based on the informal knowledges by five-year-old children. The numbers which are contained in problems consist of the numbers bigger than 5 and smaller than 10. The subjects were 21 five-year-old children who didn't learn four operations. The interview with observation was used in this research. Researcher gave the various materials to children and permitted to use them for problem solving. And researcher read the word problems to children and children solved the problems. The results are as follows: five-year-old children have the competence of problem solving in four operations word problems. They used mental computation or counting all materials strategy in addition problem. The methods of problem solving were similar to that of addition in subtraction, multiplication and division, but the rate of success was different. Children performed poor1y in division word problems. According to this research, we know that kindergarten educators should be interested in children's informal knowledges of four operations including shapes, patterns, statistics and probability. For this, it is needed to developed the curriculum and programs for informal mathematical experiences.

• The KIPS Transactions:PartB
• /
• v.11B no.4
• /
• pp.509-516
• /
• 2004

Semantic interpretation of image is incomplete without some mechanism for understanding semantic content that is not directly visible. For this reason, human assisted content-annotation through natural language is an attachment of textual description to image. However, keyword-based retrieval is in the level of syntactic pattern matching. In other words, dissimilarity computation among terms is usually done by using string matching not concept matching. In this paper, we propose a method for computerized semantic similarity calculation In WordNet space. We consider the edge, depth, link type and density as well as existence of common ancestors. Also, we have introduced method that applied similarity measurement on semantic image retrieval. To combine wi#h the low level features, we use the spatial color distribution model. When tested on a image set of Microsoft's 'Design Gallery Line', proposed method outperforms other approach.

• The KIPS Transactions:PartB
• /
• v.10B no.2
• /
• pp.229-236
• /
• 2003

Named entity recognition is the process indispensable to question answering and information extraction systems. This paper presents an HMM based named entity (m) recognition method using the construction principles of compound words. In Korean, many named entities can be decomposed into more than one word. Moreover, there are contextual relationships among nouns in an NE, and among an NE and its surrounding words. In this paper, we classify words into a word as an NE in itself, a word in an NE, and/or a word adjacent to an n, and train an HMM based on NE-related word types and parts of speech. Proposed named entity recognition (NER) system uses trigram model of HMM for considering variable length of NEs. However, the trigram model of HMM has a serious data sparseness problem. In order to solve the problem, we use multi-level back-offs. Experimental results show that our NER system can achieve an F-measure of 87.6% in the economic articles.

• Communications of Mathematical Education
• /
• v.26 no.3
• /
• pp.301-316
• /
• 2012

Ball, Thames & Phelps(2008) introduced the idea of Mathematical Knowledge for Teaching(MKT) teacher. Specialized Content Knowledge(SCK) is one of six categories in MKT. SCK is a knowledge base, useful especially for math teachers to analyze errors, evaluate alternative ideas, give mathematical explanations and use mathematical representation. The purpose of this study is to analyze the elementary teacher's SCK. 29 six graders made word problems with respect to division fraction $9/10{\div}2/5$. These word problems were classified four sentence types based on Sinicrope, Mick & Kolb(2002) and then representative four sentence types were given to 10 teachers who have taught six graders. Data analysis was conducted through the teachers' evaluation of the answers(word problems) and revision of students' mathematical errors. This study showed how to know meanings of fraction division for effective teaching. Moreover, it suggested several implications to develop SCK for teaching and learning.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.9
• /
• pp.17-27
• /
• 2012

Open Market is one of the key factors to accelerate the profit. Usually retailers sell items in several Open Market. One of the challenges for retailers is to assign categories of items with different classification systems. In this research, we propose an item category recommendation method to support appropriate products category registration. Our recommendations are based on semantic relation between existing and any other Open Market categorization. In order to analyze correlations of categories, we use Morpheme analysis, Korean Wiki Dictionary, WordNet and Google Translation API. Our proposed method recommends a category, which is most similar to a guide word by measuring semantic similarity. The experimental results show that, our system improves the system accuracy in term of search category, and retailers can easily select the appropriate categories from our proposed method.

• Journal of Digital Convergence
• /
• v.13 no.5
• /
• pp.69-78
• /
• 2015

In this study, Word-of-mouth Intention of the factors Influence the Connectivity, Convenience and Application also was Investigated. Connectivity, Convenience on the Influence of the Mediation Effect was Carried out to Examine. The test results used in this Study Established Connectivity, Convenience of Application and Word-of-mouth to the Positive Effect was Found. Also Verifying the results of the Mediating Effect of Application and Application the Mediation Effect was Verification. These Factors Result in the Application and also in Calendar, Useful Application, Video, Music, Game of Word-of-mouth Intention Influence. For this Study, the use of Smartphones is a lot of College Students Surveyed and the Findings were Derived. This result provides an application development strategy implications that can satisty the user's Smartphone Convergent times.

• Industrial Engineering and Management Systems
• /
• v.15 no.3
• /
• pp.224-230
• /
• 2016

The use of new words, numerous spoken languages, and abbreviations on the Internet is extensive. As such, automatically acquiring words for the purpose of analyzing Internet content is very difficult. In a previous study, we proposed a method for Japanese word segmentation using character N-grams. The previously proposed method is based on a simple state-transition model that is established under the assumption that the input document is described based on four states (denoted as A, B, C, and D) specified beforehand: state A represents words (nouns, verbs, etc.); state B represents statement separators (punctuation marks, conjunctions, etc.); state C represents postpositions (namely, words that follow nouns); and state D represents prepositions (namely, words that precede nouns). According to this state-transition model, based on the states applied to each pseudo-word, we search the document from beginning to end for an accessible pattern. In other words, the process of this transition detects some words during the search. In the present paper, we perform experiments based on the proposed word acquisition algorithm using Japanese and Chinese newspaper articles. These articles were obtained from Japan's Kyoto University and the Chinese People's Daily. The proposed method does not depend on the language structure. If text documents are expressed in Unicode the proposed method can, using the same algorithm, obtain words in Japanese and Chinese, which do not contain spaces between words. Hence, we demonstrate that the proposed method is language independent.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.5
• /
• pp.267-278
• /
• 2017

As the same letter can be pronounced differently depending on word contexts, one should refer to a lexicon in order to pronounce a word correctly. Phonetic alphabets that lexicons adopt as well as pronunciations that lexicons describe for the same word can be different from lexicon to lexicon. In this paper, we use a sequence-to-sequence model that is widely used in deep learning research area in order to convert automatically from one pronunciation to another. The 12 seq2seq models are implemented based on pronunciation training data collected from 4 different lexicons. The exact accuracy of the models ranges from 74.5% to 89.6%. The aim of this study is the following two things. One is to comprehend a property of phonetic alphabets and pronunciations used in various lexicons. The other is to understand characteristics of seq2seq models by analyzing an error.