• Journal of Information Technology Services
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• v.15 no.3
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• pp.71-95
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• 2016

In recent years, text mining has been used to extract meaningful insights from the large volume of unstructured text data sets of various domains. As one of the most representative text mining applications, topic modeling has been widely used to extract main topics in the form of a set of keywords extracted from a large collection of documents. In general, topic modeling is performed according to the weighted frequency of words in a document corpus. However, general topic modeling cannot discover the relation between documents if the documents share only a few terms, although the documents are in fact strongly related from a particular perspective. For instance, a document about "sexual offense" and another document about "silver industry for aged persons" might not be classified into the same topic because they may not share many key terms. However, these two documents can be strongly related from the R&D perspective because some technologies, such as "RF Tag," "CCTV," and "Heart Rate Sensor," are core components of both "sexual offense" and "silver industry." Thus, in this study, we attempted to discover the differences between the results of general topic modeling and R&D perspective topic modeling. Furthermore, we package social issues from the R&D perspective and present a prototype system, which provides a package of news articles for each R&D issue. Finally, we analyze the quality of R&D perspective topic modeling and provide the results of inter- and intra-topic analysis.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.247-253
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• 2020

It has emerged Food-content among various forms of 1-person media through social media. Food-content influencer also market products through 1-person media, generating revenue through increased views and subscribers of 1-person media. It also sells products through sponsorship. In general, there is a profit structure through 1-person media viewing, but research on how restaurant companies generate profits directly through food-content is insufficient. In addition, research on converting subscribers to consumers through food-contents is minimal. In this paper, we propose an experiential application system based on the behavior of food-content creators. The proposed system collects and categorizes food-content information, and maps between highly related words to organize into keyword categories. The ontology tag-based concept network applied to the proposed system connects representative information by pre-extracting/mapping information related to information requests among a wide range of data. This method maps relevant food-content information to provide the user with data collected/storage in the form of an application. The user uses the application while watching the food eaten by the influencer and creator. And, it is meaningful that the user could be provided is provided with information about the food they want to eat.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.521-526
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• 2017

Data format of Big data is diverse and vast, and its generation speed is very fast, requiring new management and analysis methods, not traditional data processing methods. Textual mining techniques can be used to extract useful information from unstructured text written in human language in online documents on social networks. Identifying trends in the message of politics, economy, and culture left behind in social media is a factor in understanding what topics they are interested in. In this study, text mining was performed on online news related to a given keyword using topic - oriented analysis technique. We use Latent Dirichiet Allocation (LDA) to extract information from web documents and analyze which subjects are interested in a given keyword, and which topics are related to which core values are related.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.157-162
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• 2008

This paper presents a learning method of tagging ontology using large tagging data such as a folksonomy, which stands for classification structure informally created by the people. There is no common agreement about the semantics of a tagging, and most social web sites internally use different methods to represent tagging information, obstructing interoperability between sites and the automated processing by software agents. To solve this problem, we need a tagging ontology, defined by analyzing intrinsic attributes of a tagging. Through several machine learning for tagging data, tag groups and similar user groups are extracted, and then used to learn the tagging ontology. A recommender system adopting the tagging ontology is also suggested as an applying field.

• Journal of Intelligence and Information Systems
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• v.15 no.2
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• pp.75-95
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• 2009

The aim of this research is to design and analyze a social network service model using mobile RFID based business card. This paper suggests how the behavior of exchanging business cards will be changed in ubiquitous environment and designs a social networking service model using a ubiquitous business card, which embeds a RFID tag. We describe the scenarios and analyze a role, value and potential benefits of participants of the u-SNS service model. For the proof of the superiority and the feasibility of our model, we compare it with its related researches and products based on the calculation of the benefits and costs of the alternatives.

• Journal of KIISE
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• v.43 no.1
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• pp.47-53
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• 2016

While the Internet develops rapidly, a huge amount of image data collected from smart phones, digital cameras and black boxes are being shared through social media sites. Generally, social images are handled by tagging them with information. Due to the ease of sharing multimedia and the explosive increase in the amount of tag information, it may be considered too much hassle by some users to put the tags on images. Image retrieval is likely to be less accurate when tags are absent or mislabeled. In this paper, we suggest a method of extracting tags from social images by using image content. In this method, CNN(Convolutional Neural Network) is trained using ImageNet images with labels in the training set, and it extracts labels from instagram images. We use the extracted labels for automatic image tagging. The experimental results show that the accuracy is higher than that of instagram retrievals.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.214-220
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• 2021

With the rapid spread of smartphones, it has become common to listen to music everywhere, just like background music in life, so it is necessary to create a music database that can make recommendations according to individual circumstances and conditions. This paper proposes a music recommendation model through social media. Since emotions, situations, time of day, weather, etc. are included in hashtags, it is possible to build a social media-based database that reflects the opinions of various people with collective intelligence. We use web crawling to collect and categorize different hashtags from posts with music title hashtags to use real listeners' opinions about music in a database. Data from social media is used to create a music database, and music is classified in a different way from collaborative filtering, which is mainly used by existing music platforms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.345-353
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• 2021

This study examined the effects of social capital on psychological identity and practical wellbeing for the Korean baby boom generation. To achieve this, an empirical survey was carried out on baby boomers who use elderly welfare centers and cultural centers living in D City. The overall research results showed that trust (t=6.893, p<.05), participation (t=5.157, p<.05), network (t=8.093, p<.05), and norm and reciprocity (t=4.787, p<.05), as sub-factors of social capital for baby boomers, had a significant effect on their practical wellbeing. Psychological identity was moderated (t=2.023, p<.05) in the effect of trust on practical wellbeing, adopting the hypothesis. This means that the social ties and the strong trust relationship between family members and relatives, which built up amid rapid economic growth, work with positive expectations of social capital and have a major effect on practical wellbeing. Moreover, practical welling also rated high, along with the high trust relationship and psychological identity. Consequently, various exchange programs and group and volunteer activity programs for baby boomers should be established to decrease their psychological identity due to the loss of social roles. Moreover, the decline of activities at a time of retirement can slow practical wellbeing.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.11a
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• pp.35-40
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• 2008

As the environmental pollution by the drastic increase of vehicles becomes one of the social major concerns, the method of reducing the harmful exhaust emission is being the subject of interest. Utilization of used frying oil as a raw material for biodiesel production is helpful not only for the stable supply of raw materials but also costing down the biodiesel price. This study was conducted the measurement the combustion and thermal characteristics with mixing ratio of biodiesel/diesel fuel. In this study, flash points and fire points were measured by using Tag Closed cup apparatus and Cleveland open cup apparatus. As the result, flash points, fire points and AIT increased with percentage of more contained biodiesel.

• Journal of Information Technology Services
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• v.13 no.2
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• pp.83-97
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• 2014

With NFC technology, visitors can easily enjoy exhibit-related information and services. The participating firms can accumulate the visitor data and build up networks with potential visitors. This paper is to report an implementation and operation case of an NFC-based exhibition support service which creates new value as above. For this objective, we introduce the issues in constructing NFC-based exhibition support service. Moreover, we analyze visitor behaviors based on the tag touch data collected, and calculate the economic values generated. The NFC-based exhibition support service in this paper was applied to Hyundai Motors' booth in the 2013 Seoul Motor Show. This paper concludes with implications for business operators that are interested in applying NFC technology to exhibition spaces.