• Review of Culture and Economy
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• v.17 no.2
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• pp.3-28
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• 2014

The characteristics of performing arts differ from those of utilitarian goods in terms of economics. Factors other than price need to be considered to understand the demand for performing arts. Audience surveys as well as econometric demand studies have confirmed that socio-economic factors such as age, income, employment, and education are major determinants of the demand for performing arts. This study focused on the attributes of concerts rather than consumer characteristics to determine the concerts audiences select in terms of transaction cost. Genre, price, internet search trends, and the purpose of performance as well as price are tested as determinants of demand by using the data set for a major concert hall in Seoul. Genre and the specific purpose of concerts influence the demand for concerts. Internet search trends of the performer are used as indicators of popularity and information exposure, which are positively correlated with demand. This result supports the hypothesis that larger audiences would attend concerts that require lower information search costs. To note, price has a positive effect on demand in the higher price range, which means that concerts at higher prices attract larger audiences, whereas normal goods have a negative slope in the demand curve. This result can be explained by the hypothesis that consumers use price as an indicator of the quality expected of a concert. Transaction cost for selecting classical concerts thus forms an inverse-U shape curve against ticket price. These results provide some explanation of why audiences of classical music choose to attend concerts at high ticket prices while offering evidence in favor of the hypothesis that performing arts are selected in a social context.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.131-146
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• 2022

The purpose of this study is to examine the locational characteristics of cafes in Jeju Island and the changes. For the purpose, we identify the spatial distribution patterns of openings and closings by period from the first opening of cafes in Jeju Island to the present. In particular, we analyze the spatial distribution characteristics found in the locations of cafes that have been opened and closed after the outbreak of COVID-19, in which new stores have significantly increased. In addition, we identify the regional attributes and the influence of online that have affected the distribution of currently open cafes and cafes that have opened or closed during the COVID-19 outbreak. As a result of empirical analysis, Jeju Island is a tourist destination and island region with the characteristics of determining major destinations through information search, showing a different distribution form from the location of cafes in inland cities. In particular, as a result of frequency analysis by extracting keyword search volume for cafes in Jeju Island, online accessibility such as information search for new areas and places in Jeju Island has become more diversified and expanded after COVID-19. In addition, as a result of calculating the distance to cafes by road size, the relationship between physical location and road accessibility, which has traditionally been an important factor, was relatively low. This study is meaningful in that it revealed the distribution patterns and characteristics of cafe locations in Jeju Island by reflecting the influence of online and offline.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.189-196
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• 2022

Skyline query is a scheme for exploring objects that are suitable for user preferences based on multiple attributes of objects. Existing skyline queries return search results as batch processing, but the need for real-time search results has increased with the advent of interactive apps or mobile environments. Online algorithm for Skyline improves the return speed of objects to explore preferred objects in real time. However, the object navigation process requires unnecessary navigation time due to repeated comparative operations. This paper proposes a Pre-processing Online Algorithm for Skyline Query (POA) to eliminate unnecessary search time in Online Algorithm exploration techniques and provide the results of skyline queries in real time. Proposed techniques use the concept of range-limiting to existing Online Algorithm to perform pretreatment and then eliminate repetitive rediscovering regions first. POAs showed improvement in standard distributions, bias distributions, positive correlations, and negative correlations of discrete data sets compared to Online Algorithm. The POAs used in this paper improve navigation performance by minimizing comparison targets for Online Algorithm, which will be a new criterion for rapid service to users in the face of increasing use of mobile devices.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• Journal of the Korean Society for Library and Information Science
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• v.46 no.2
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• pp.261-280
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• 2012

This study seeks to replace PaRIS Principles and find directions of revising KCR4 by analyzing the international Cataloging Principles 2009(ICP 2009) established in the environment of Machine Readable Cataloging. ICP 2009 was reflected in cataloging rules such as RDA and ISBD 2010 as the minimal principles for uniformity in establishing each nation's cataloging rules. In contrary, KCR4 needs to be revised because it has never been changed after 2003, and has only description rules without any rules for the choice and forms of access points. Therefore, this study aims to grasp requirements that should be reflected in KCR4 through analyzing ICP 2009. In first step, it is to grasp the features of ICP 2009 by comparing PaRIS Principle and ICP 2009 and to compare KCR4 in aspects of ICP 2009. The detailed elements for comparison between ICP 2009 and KCR4 are scope, general principles, entitles, attributes, and relationships, objectives and functions of the catalogue, bibliographic description, access points, foundations for search capabilities as the contents of ICP 2009. As a result, this study could give some directions of KCR4 in the future. First, ISBD 2010 and conceptual models should be reflected in KCR4 in description. Second, it should regulate the authority access points in KCR4 based on ICP 2009. Third, it will describe essential access points of work and expression attributes in bibliographic records and authority records to find works and expression. This study will contribute to guide the national cataloging rules.

• Management & Information Systems Review
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• v.38 no.2
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• pp.83-103
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• 2019

Supply chain management(SCM) requires efforts to search for methods for mutual growth with partner companies and to maintain continuous cooperative relations in order to gain a competitive edge. Because information competencies play a big role within the supply chain, it is essential to examine the relationship of information sharing and partnership quality that can affect information competency. In order to maintain continuous business relations between partner companies, it is necessary to identify the obstacles with partner companies resulting from the imbalance of power within a supply chain and to take on a strategic approach for effectively managing such obstacles. Therefore, there is a significant need to discuss strategic approach methods to enable the logic of mutual growth through the CSV that is worth learning from the partner company and the attributes of non-mediated power. CSV will be reviewed from various aspects as a new management paradigm in the future. This study aims at suggesting a continuous growth model for companies by solving social problems through the integration of CSV and the concept of non-mediated power to advance the information competencies of SCM. A total of 142 copies of survey forms for SCM Implementation Companies were using the PLS structural equation modeling for an analysis, and the following are the findings. Results of this study showed that both CSV and non-mediated power had significant impact on information sharing and partnership qualities, and the conclusion that it is possible to enhance information competency through information sharing and partnership quality. Based on this, this study proposes the implication that it is necessary to elevate awareness of CSV and non-mediated power as variables for the coexistence of SCM participating companies.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.4
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• pp.299-314
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• 2017

Technological advances in media have expanded users' consciousness. At the same time, users have changed from passive into active voice by interacting media. The emergence of mobile made different structures and contents compared to the past. Especially, Korean culture of mobile converted original media channels to contents in a category. Plus, the usage structure of internet of this time converges in massive portal sites. It is because that the structure has aspect of emitting through remediation in the sites. Also, Korean massive portal sites have provided specific service named 'real-time issues'. This is not only the unique way of offering information that exists in Korea but also high usability of getting issues. We therefore considered the meaning of durability of real-time issues in the view of journalism, compared original media channels. Then, this paper identified the user attributes for acquisition of information following ways using informal and formal data from Korean massive portal sites named 'Daum' and 'Naver'.

• Korean Journal of Social Welfare Studies
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• v.41 no.3
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• pp.135-162
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• 2010

The Purpose of this study is to get basic material about voluntary association in local community and its utilization. In order to achieve the purpose of this study, it was considered that trust of social capital plays a leading part in voluntary association to maintain or strengthen its role and activities. For this reason we attempt to find the process of trust building in voluntary association. The revised ground theory that is complementary weaknesses of ground theory is used in this study and in 11months, four times researches have investigated. As a result, it was analyzed that the structure of building trust can be categorized into three structure, building up relationship, dynamic interaction and structural stabilization in voluntary association. In the space that is structured spatially and temporal, role, activity, accomplishment, attitude, conflict and environment acted as basic attributes. These attributes can be found in every building process of trust and influence on continuance and growth of voluntary association. The fact that this study offers in-depth understanding of voluntary association and empirical directivity regarding the community welfare services is of great significant.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.1
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• pp.9-20
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• 2005

Recently, the MPEG-7 standard a multimedia content description standard is wide]y used for content based image/video retrieval systems. However, since the descriptors standardized in MPEG-7 are usually multidimensional and the problem called 'Curse of dimensionality', previously proposed indexing methods(for example, multidimensional indexing methods, dimensionality reduction methods, filtering methods, and so on) could not be used to effectively index the multimedia database represented in MPEG-7. This paper proposes an efficient multimedia data indexing mechanism reflecting the characteristics of MPEG-7 visual descriptors. In the proposed indexing mechanism, the descriptor is transformed into a histogram of some attributes. By representing the value of each bin as a binary number, the histogram itself that is a visual descriptor for the object in multimedia database could be represented as a bit string. Bit strings for all objects in multimedia database are collected to form an index file, bitmap index, in the proposed indexing mechanism. By XORing them with the descriptors for query object, the candidate solutions for similarity search could be computed easily and they are checked again with query object to precisely compute the similarity with exact metric such as Ll-norm. These indexing and searching mechanisms are efficient because the filtering process is performed by simple bit-operation and it reduces the search space dramatically. Upon experimental results with more than 100,000 real images, the proposed indexing and searching mechanisms are about IS times faster than the sequential searching with more than 90% accuracy.