• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.139-152
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• 2011

Recommender systems have become an important research field since the emergence of the first paper on collaborative filtering in the mid-1990s. In general, recommender systems are defined as the supporting systems which help users to find information, products, or services (such as books, movies, music, digital products, web sites, and TV programs) by aggregating and analyzing suggestions from other users, which mean reviews from various authorities, and user attributes. However, as academic researches on recommender systems have increased significantly over the last ten years, more researches are required to be applicable in the real world situation. Because research field on recommender systems is still wide and less mature than other research fields. Accordingly, the existing articles on recommender systems need to be reviewed toward the next generation of recommender systems. However, it would be not easy to confine the recommender system researches to specific disciplines, considering the nature of the recommender system researches. So, we reviewed all articles on recommender systems from 37 journals which were published from 2001 to 2010. The 37 journals are selected from top 125 journals of the MIS Journal Rankings. Also, the literature search was based on the descriptors "Recommender system", "Recommendation system", "Personalization system", "Collaborative filtering" and "Contents filtering". The full text of each article was reviewed to eliminate the article that was not actually related to recommender systems. Many of articles were excluded because the articles such as Conference papers, master's and doctoral dissertations, textbook, unpublished working papers, non-English publication papers and news were unfit for our research. We classified articles by year of publication, journals, recommendation fields, and data mining techniques. The recommendation fields and data mining techniques of 187 articles are reviewed and classified into eight recommendation fields (book, document, image, movie, music, shopping, TV program, and others) and eight data mining techniques (association rule, clustering, decision tree, k-nearest neighbor, link analysis, neural network, regression, and other heuristic methods). The results represented in this paper have several significant implications. First, based on previous publication rates, the interest in the recommender system related research will grow significantly in the future. Second, 49 articles are related to movie recommendation whereas image and TV program recommendation are identified in only 6 articles. This result has been caused by the easy use of MovieLens data set. So, it is necessary to prepare data set of other fields. Third, recently social network analysis has been used in the various applications. However studies on recommender systems using social network analysis are deficient. Henceforth, we expect that new recommendation approaches using social network analysis will be developed in the recommender systems. So, it will be an interesting and further research area to evaluate the recommendation system researches using social method analysis. This result provides trend of recommender system researches by examining the published literature, and provides practitioners and researchers with insight and future direction on recommender systems. We hope that this research helps anyone who is interested in recommender systems research to gain insight for future research.

• 대한공업교육학회지
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• v.37 no.1
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• pp.183-204
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• 2012

This study was to analysis perception about Teaching & Learning Support System of the school of Rural Areas in Korea. In order to accomplish the study purpose, the study conducted a research through Web Survey method and examined their recognition. Major findings of this study were as follows: First, Student was satisfied with TLSS of the school of Rural Areas in Korea. Students would like to 'using e-learning with Electronic board and Tablet PC' among program contents. But the system' utilization was low. However, 90% of the students wanted that teacher usually using the FASTEL. Second, Teacher satisfaction was lower compared to the students is relatively. Teachers prefer 'various after school program' to 'using e-learning with Electronic board and Tablet PC'. However, learning effective of using FASTEL system was a 73.8% of teachers are effective is aware and had. Third, 35% Students recognized that are using the pastel system, frequently, On the other hand, the teachers are 60% and to recognize that there was. The reason doesn't the system to good use is slow wireless. Still, e-learning classroom infrastructure for satisfaction was high. Fourth, Teachers recognized students and the pastel system interaction than other e-learning system high. FASTEL System used in the most uncomfortable things on e-learning classroom Wireless Internet phenomena and lost content lacking, in order, I was told. Therefore, there is an urgent need to improve to include Wireless Internet speed improvements and various content added support, easy-to-use instructional tools Add support order selected.

• Journal of Korean Home Economics Education Association
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• v.32 no.2
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• pp.59-76
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• 2020

The purpose of this study was to develop and evaluate the teaching/learning process plan of 'housing culture and practical space use' for home economics in middle school according to the problem based learning(PBL) model. The plan consisting of 4-lessons has been developed and implemented following the steps of ADDIE model. Various activity materials (4 scenarios, 6 individual activity sheets, 10 reading texts, and 5 working resources) and visual materials (4 sets of ppt and 4 moving pictures) as well as questionnaire were developed for the 4-session lessons. The plans were implemented to a single class of 21 junior students at H middle school in rural area, Kyeongnam, from 1^st to 12^th of April, 2019. Students highly enjoyed and were satisfied with the whole 4-lessons in aspects such as understanding of the contents, adequacy of materials and activities, and usefulness in one's own daily life. Additionally, they have more actively participated in the lessons than usual and even interested in learning more of such lessons. Students also reported that they highly accomplished the goal of each lesson as well as overall objectives. They showed interest in the major part of PBL lesson such as scenario and group activities. And they engaged themselves in drawing the share housing space plan with '5D planner' web program which they described as the best part of the lessons. The teaching/learning process plan developed in this study may be used as a theme of maker education, which is emerging these days. It can be concluded that the PBL teaching/learning process plans for 'housing values and practical space use' would contribute to improving students' attitude on living with others and ability to manage one's individual life.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.113-145
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• 2008

Marketing for the distribution industry is making an ongoing progress in the changes of customers, the competitive environment, and the internal marketing environment. Integrated marketing communication activities are required for the enhancement of efficiency in the market.oriented activities. In this study, IMC is defined as "a notion that a market oriented business integrated marketing communication means, conducting and evaluating marketing activities with consistent messages in order to communicate with customers based on databases." In this study, an IMC planning model for the improvement of marketing efficiency in the distribution industry was derived from a pilot study. This model may be broken down into the following phases: IMC goals setting, situational analysis (customer analysis, competition analysis and company analysis), customer data analysis, contact management, budgeting, the establishment of an IMC strategy, the IMC mix and execution, an evaluation system, and feedback. In consideration of the characteristics of the distribution industry, this study was accompanied by a vocational study on IMC means employed by, in particular, department stores and other distributors such as: advertising, sales promotion, sales promotion advertising, direct marketing, public relations, personal selling, the Internet, mobile, visual merchandising, words of mouth. In addition, this study also covered the correlation among variables such as IMC activities of distributors, the process of forming customer's brand attitudes, brand loyalty and repurchase intention. This research would enhance the utilization of IMC. The analysis on customer's brand attitudes toward the IMC activities of distributors requires the simultaneous consideration of how they are linked to purchase as well as their attitudes toward both distributors and stores. The formation of brand loyalty and repurchase intention is related to the integration of marketing communication and the maintenance of consistency in contents, which requires integrated brand communication (IBC) strategies. IBC is a concept of using IMC means to manage the brand in a continuing and consistent manner and measuring their effect, which is a process to establish enterprise.level brand identity and maximize brand loyalty and repurchase intention by integrating IMC means. For an empirical analysis in this study, an online questionnaire survey was conducted among those department store customers from 20's to 50's who reside either in the Seoul and Gyeonggi areas and have made purchase at department stores. In this study, the research model consisted of four theoretical variables: IMC activities, IMC attitudes, brand loyalty, and repurchase intention, on which variables a pilot study was conducted. A number of hypotheses were constructed on the relations between IMC activities and IMC attitudes, between IMC attitudes and repurchase intention, and between brand loyalty and repurchase intention. The test of the hypotheses may be summarized as follows: Firstly, the test of the hypothesis concerning the relation between IMC attitudes and IMC activities - advertising, sales promotion, direct marketing, public relations, personal selling, the Web, mobile, visual merchandising, and word of mouth - indicates that advertising, sales promotion, direct marketing, public relations, personal selling, mobile, visual merchandising, and word of mouth have significant impact on IMC activities. In addition to the result similar to those of previous studies that such marketing communication means as word of mouth, advertising, personal selling and sales promotion, in particular, play very important roles, a notable finding of this study is that visual merchandising performed by department stores is shown to have very significant impact on IMC activities. On a separate note, it is also noteworthy that Internet marketing activities engaged by department stores are not shown to have significant impact on IMC attitudes. Secondly, the test of the hypothesis on the relation between IMC attitudes and brand loyalty attests that IMC attitudes for the distribution industry significantly affect brand loyalty. Thirdly, the test of the hypothesis concerning the relation between IMC attitudes and repurchase intention confirms that IMC attitudes for the distribution industry significantly affect repurchase intention. Fourthly, the test of the hypothesis concerning the relation between brand loyalty and repurchase intention indicates that brand loyalty significantly affect repurchase intention. A comprehensive view of these findings points to the conclusion that the IMC activities for the distribution industry do affect IMC attitudes, brand loyalty, and repurchase intention.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.81-96
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• 2013

Video information retrieval has become a very important issue because of the explosive increase in video data from Web content development. Meanwhile, content-based video analysis using visual features has been the main source for video information retrieval and browsing. Content in video can be represented with content-based analysis techniques, which can extract various features from audio-visual data such as frames, shots, colors, texture, or shape. Moreover, similarity between videos can be measured through content-based analysis. However, a movie that is one of typical types of video data is organized by story as well as audio-visual data. This causes a semantic gap between significant information recognized by people and information resulting from content-based analysis, when content-based video analysis using only audio-visual data of low level is applied to information retrieval of movie. The reason for this semantic gap is that the story line for a movie is high level information, with relationships in the content that changes as the movie progresses. Information retrieval related to the story line of a movie cannot be executed by only content-based analysis techniques. A formal model is needed, which can determine relationships among movie contents, or track meaning changes, in order to accurately retrieve the story information. Recently, story-based video analysis techniques have emerged using a social network concept for story information retrieval. These approaches represent a story by using the relationships between characters in a movie, but these approaches have problems. First, they do not express dynamic changes in relationships between characters according to story development. Second, they miss profound information, such as emotions indicating the identities and psychological states of the characters. Emotion is essential to understanding a character's motivation, conflict, and resolution. Third, they do not take account of events and background that contribute to the story. As a result, this paper reviews the importance and weaknesses of previous video analysis methods ranging from content-based approaches to story analysis based on social network. Also, we suggest necessary elements, such as character, background, and events, based on narrative structures introduced in the literature. We extract characters' emotional words from the script of the movie Pretty Woman by using the hierarchical attribute of WordNet, which is an extensive English thesaurus. WordNet offers relationships between words (e.g., synonyms, hypernyms, hyponyms, antonyms). We present a method to visualize the emotional pattern of a character over time. Second, a character's inner nature must be predetermined in order to model a character arc that can depict the character's growth and development. To this end, we analyze the amount of the character's dialogue in the script and track the character's inner nature using social network concepts, such as in-degree (incoming links) and out-degree (outgoing links). Additionally, we propose a method that can track a character's inner nature by tracing indices such as degree, in-degree, and out-degree of the character network in a movie through its progression. Finally, the spatial background where characters meet and where events take place is an important element in the story. We take advantage of the movie script to extracting significant spatial background and suggest a scene map describing spatial arrangements and distances in the movie. Important places where main characters first meet or where they stay during long periods of time can be extracted through this scene map. In view of the aforementioned three elements (character, event, background), we extract a variety of information related to the story and evaluate the performance of the proposed method. We can track story information extracted over time and detect a change in the character's emotion or inner nature, spatial movement, and conflicts and resolutions in the story.

• Korean Journal of Food Science and Technology
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• v.37 no.5
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• pp.768-775
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• 2005

Lentinus edodes powder was added at 1-3%(w/w) to improve functional properties of jocheong. Content of crude protein, ash, crude lipids, total mineral, free sugar and reducing sugar increased with increasing amount of L. edodes powder, while viscosity and solid and carbohydrate contents decreased. Through amino acid analysis, 17 amino acids were identified and quantified, glutamic acid being the major amino acid. No significant differences were observed in fatty acid composition and pH between control and L. edodes powder-added jocheong. Addition of mushroom powder in jocheong decreased lightness, yellowness and redness in Hunter's color value. Sensor score of jucheong containing 1% of L. edodes powder was similar to that of control. Results showed jocheong containing less than 2% L. edodes powder gave highest scores in quality characteristics and sensory evaluation.

• Cartoon and Animation Studies
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• s.36
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• pp.469-491
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• 2014

Webtoon has developed the method that makes it possible to express sound visually. Also we can also hear sound in webtoon through the development of web technology. It is natural that we analyze the sound that we can hear, but we can also analyze the sound that we can not hear. This study is based on 'dual code' in cognitive psychology. Cartoonists can make visual expression on the basis of auditive impression and memory, and readers can recall the sound through the process of memory and memory-retrieval. This study analyzes both audible sound and inaudable sound. Concise analysis owes the method to film sound theory. Three main factor, Volume, pitch, and tone are recognized by frequency in acoustics. On the other hand they are expressed by the thickness and site of line and image of sound source. The visual expression of in screen sound and off screen sound is related to the frame of comics. Generally the outside of frame means off sound, but some off sound is in the frame. In addition, horror comics use much sound for the effect of genre like horror film. When analyzing comics sound using this kinds of the method film sound analysis, we can find that webtoon has developed creative expression method comparing with simple ones of early comics. Especially arranging frames and expressing sound following and vertical moving are new ones in webtoon. Also types and arrangement of frame has been varied. BGM is the first in using audible sound and recently BGM composed mixing sound effect is being used. In addition, the program which makes it possible for readers to hear sound according to scroll moving. Especially horror genre raise the genre effects using this technology. Various methods of visualizing sound are being created, and the change shows that webtoon could be the model of convergence in contents.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.101-116
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• 2015

Recently, due to the development of smart devices and social media, vast amounts of information with the various forms were accumulated. Particularly, considerable research efforts are being directed towards analyzing unstructured big data to resolve various social problems. Accordingly, focus of data-driven decision-making is being moved from structured data analysis to unstructured one. Also, in the field of recommendation system, which is the typical area of data-driven decision-making, the need of using unstructured data has been steadily increased to improve system performance. Approaches to improve the performance of recommendation systems can be found in two aspects- improving algorithms and acquiring useful data with high quality. Traditionally, most efforts to improve the performance of recommendation system were made by the former approach, while the latter approach has not attracted much attention relatively. In this sense, efforts to utilize unstructured data from variable sources are very timely and necessary. Particularly, as the interests of users are directly connected with their needs, identifying the interests of the user through unstructured big data analysis can be a crew for improving performance of recommendation systems. In this sense, this study proposes the methodology of improving recommendation system by measuring interests of the user. Specially, this study proposes the method to quantify interests of the user by analyzing user's internet usage patterns, and to predict user's repurchase based upon the discovered preferences. There are two important modules in this study. The first module predicts repurchase probability of each category through analyzing users' purchase history. We include the first module to our research scope for comparing the accuracy of traditional purchase-based prediction model to our new model presented in the second module. This procedure extracts purchase history of users. The core part of our methodology is in the second module. This module extracts users' interests by analyzing news articles the users have read. The second module constructs a correspondence matrix between topics and news articles by performing topic modeling on real world news articles. And then, the module analyzes users' news access patterns and then constructs a correspondence matrix between articles and users. After that, by merging the results of the previous processes in the second module, we can obtain a correspondence matrix between users and topics. This matrix describes users' interests in a structured manner. Finally, by using the matrix, the second module builds a model for predicting repurchase probability of each category. In this paper, we also provide experimental results of our performance evaluation. The outline of data used our experiments is as follows. We acquired web transaction data of 5,000 panels from a company that is specialized to analyzing ranks of internet sites. At first we extracted 15,000 URLs of news articles published from July 2012 to June 2013 from the original data and we crawled main contents of the news articles. After that we selected 2,615 users who have read at least one of the extracted news articles. Among the 2,615 users, we discovered that the number of target users who purchase at least one items from our target shopping mall 'G' is 359. In the experiments, we analyzed purchase history and news access records of the 359 internet users. From the performance evaluation, we found that our prediction model using both users' interests and purchase history outperforms a prediction model using only users' purchase history from a view point of misclassification ratio. In detail, our model outperformed the traditional one in appliance, beauty, computer, culture, digital, fashion, and sports categories when artificial neural network based models were used. Similarly, our model outperformed the traditional one in beauty, computer, digital, fashion, food, and furniture categories when decision tree based models were used although the improvement is very small.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.61-83
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• 2012

A knowledge map describes the network of related knowledge into the form of a diagram, and therefore underpins the structure of knowledge categorizing and archiving by defining the relationship of the referential navigation between knowledge. The referential navigation between knowledge means the relationship of cross-referencing exhibited when a piece of knowledge is utilized by a user. To understand the contents of the knowledge, a user usually requires additionally information or knowledge related with each other in the relation of cause and effect. This relation can be expanded as the effective connection between knowledge increases, and finally forms the network of knowledge. A network display of knowledge using nodes and links to arrange and to represent the relationship between concepts can provide a more complex knowledge structure than a hierarchical display. Moreover, it can facilitate a user to infer through the links shown on the network. For this reason, building a knowledge map based on the ontology technology has been emphasized to formally as well as objectively describe the knowledge and its relationships. As the necessity to build a knowledge map based on the structure of the ontology has been emphasized, not a few researches have been proposed to fulfill the needs. However, most of those researches to apply the ontology to build the knowledge map just focused on formally expressing knowledge and its relationships with other knowledge to promote the possibility of knowledge reuse. Although many types of knowledge maps based on the structure of the ontology were proposed, no researches have tried to design and implement the referential navigation-enabled knowledge map. This paper addresses a methodology to build the ontology-based knowledge map enabling the referential navigation between knowledge. The ontology-based knowledge map resulted from the proposed methodology can not only express the referential navigation between knowledge but also infer additional relationships among knowledge based on the referential relationships. The most highlighted benefits that can be delivered by applying the ontology technology to the knowledge map include; formal expression about knowledge and its relationships with others, automatic identification of the knowledge network based on the function of self-inference on the referential relationships, and automatic expansion of the knowledge-base designed to categorize and store knowledge according to the network between knowledge. To enable the referential navigation between knowledge included in the knowledge map, and therefore to form the knowledge map in the format of a network, the ontology must describe knowledge according to the relation with the process and task. A process is composed of component tasks, while a task is activated after any required knowledge is inputted. Since the relation of cause and effect between knowledge can be inherently determined by the sequence of tasks, the referential relationship between knowledge can be circuitously implemented if the knowledge is modeled to be one of input or output of each task. To describe the knowledge with respect to related process and task, the Protege-OWL, an editor that enables users to build ontologies for the Semantic Web, is used. An OWL ontology-based knowledge map includes descriptions of classes (process, task, and knowledge), properties (relationships between process and task, task and knowledge), and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. Therefore a knowledge network can be automatically formulated based on the defined relationships, and the referential navigation between knowledge is enabled. To verify the validity of the proposed concepts, two real business process-oriented knowledge maps are exemplified: the knowledge map of the process of 'Business Trip Application' and 'Purchase Management'. By applying the 'DL-Query' provided by the Protege-OWL as a plug-in module, the performance of the implemented ontology-based knowledge map has been examined. Two kinds of queries to check whether the knowledge is networked with respect to the referential relations as well as the ontology-based knowledge network can infer further facts that are not literally described were tested. The test results show that not only the referential navigation between knowledge has been correctly realized, but also the additional inference has been accurately performed.

• The Korean Journal of Archival Studies
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• no.16
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• pp.147-200
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• 2007

Archives provide users with easier and more convenient access to and use of archival data through their Internet websites. Now, archival websites function not only as a tool of information provision or marketing, or as a gateway of Internet-based materials, but also as cyber space for all services of archives, providing users with information and knowledge and direct accessibility to the services in the archives. At present, Korean archives are proceeding with establishing websites or upgrading existing websites, and the use rates and reliability of web services by users are becoming higher. However, although there have been various studies for the evaluation of general websites, few are found with regard to the evaluation of archival websites. It is necessary for archival websites that provide information service to users of every stripe to make more efforts and have more interest in user-centered convenience, right to know, and information provision-centered service. Accordingly, needless to say, it is necessary to study evaluation criteria of websites so that high quality archival websites can be established. With this background, this study establishes evaluation criteria for archival websites, which are appropriate to their objectives and functions and directly evaluates archives, presenting ways to establish and redevelop archival websites. More detailed purposes are as follows: First, analyzes existing theories of evaluation through reviews on previous literature and elicits evaluation criteria for websites, which are appropriate to archives; Second, based on the elicited evaluation criteria for archival websites, examines the current state of domestic archival websites through analytic evaluation; and Third, presents ways to improve archival websites that may be helpful in establishing or improving them in the future. The expectancy effects of this study are as follows: First, it will be helpful when one wishes to identify the current state of archival websites and to improve or redevelop existing websites, or to develop online service through website; Second, it will function as a checklist when a developer who is to establish an archival website wishes to develop evaluation criteria; and Third, it may be used as an inspection tool when an archives contracts out the establishment of its website.