• Journal of the Korea Society of Computer and Information
• /
• v.28 no.12
• /
• pp.41-48
• /
• 2023

In this paper, we propose an analysis of recent trends in the NFT (Non-Fungible Token) industry using topic modeling techniques, focusing on their universal application across various industrial fields. For this study, patent data was utilized to understand industry trends. We collected data on 371 domestic and 454 international NFT-related patents registered in the patent information search service KIPRIS from 2017, when the first NFT standard was introduced, to October 2023. In the preprocessing stage, stopwords and lemmas were removed, and only noun words were extracted. For the analysis, the top 50 words by frequency were listed, and their corresponding TF-IDF values were examined to derive key keywords of the industry trends. Next, Using the LDA algorithm, we identified four major latent topics within the patent data, both domestically and internationally. We analyzed these topics and presented our findings on NFT industry trends, underpinned by real-world industry cases. While previous review presented trends from an academic perspective using paper data, this study is significant as it provides practical trend information based on data rooted in field practice. It is expected to be a useful reference for professionals in the NFT industry for understanding market conditions and generating new items.

• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.109-122
• /
• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Ginseng Culture
• /
• v.4
• /
• pp.13-37
• /
• 2022

Even before recorded history, the Korean people took ginseng. Later, poetry passed down from China developed into a literary style in which intellectuals from the Silla, Goryeo, and Joseon Dynasties expressed their thoughts concisely. The aim of this paper is to find Korean poems related to ginseng and to look for their semantic network. To this end, "Korea Classical DB ", produced by the Institute for the Translation of Korean Classics, was searched to find ginseng poems. As the result of a search in November 2021, two poems from the Three Kingdoms Period, two poems from the Goryeo Dynasty, and 23 poems from the Joseon Dynasty were searched. An examination of these poems found that the first ginseng poem was "Goryeoinsamchan," which was sung by people in Goguryeo around the 6th century. Ginseng poetry during the Goryeo Dynasty is represented by Anchuk's poem. Anchuk sang about the harmful effects of ginseng tributes from a realistic point of view. Ginseng poetry in the Joseon Dynasty is represented by Seo Geo-jeong in the early period and Jeong Yakyong in the late period. Seo Geo-jeong's ginseng poem is a romantic poem that praises the mysterious pharmacological effects of ginseng. A poem called "Ginseng" by Yongjae Seonghyeon is also a romantic poem that praises the mysterious medicinal benefits of ginseng. As a scholar of Realist Confucianism, Dasan Jeong Yak-yong wrote very practical ginseng poems. Dasan left five ginseng poems, the largest number written by one poet. Dasan tried ginseng farming himself and emerged from the experience as a poet. The story of the failure and success of his ginseng farming was described in his poems. At that time, ginseng farming was widespread throughout the country due to the depletion of natural ginseng and the development of ginseng farming techniques after the reign of King Jeongjo. Since the early 19th century, ginseng farming had been prevalent on a large scale in the Gaeseong region, and small-scale farming had also been carried out in other regions. What is unusual is Kim Jin-soo's poem. At that time, in Tong Ren Tang, Beijing (the capital of the Qing Dynasty), ginseng from Joseon sold well under the "Songak Sansam" brand. Kim Jin-Soo wrote about this brand of ginseng in his poem. In 1900, Maecheon Hwanghyeon also created a ginseng poem, written in Chinese characters. Thus, the semantic network of Korean ginseng poems is identified as follows: 1) Ginseng poetry in the spirit of the people - Emerging gentry in the Goryeo Dynasty (Anchuk). 2) Romantic ginseng poetry - Government School in the early Joseon Dynasty (Seo Geo-jeong, Seonghyeon, etc.). 3) Practical ginseng poetry - Realist School in the late Joseon Dynasty (Jeong Yak-yong, Kim Jin-soo, Hwang Hyun, etc.). This semantic network was extracted while examining the development of Korean ginseng poems.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.47 no.4
• /
• pp.33-49
• /
• 2019

The purpose of this study was to investigate the changes in the experiences of visitors of Yeonnam-dong during the period covering the development of a linear park, the Gyeongui Line Park. This study used a text mining technique to analyze Naver Blog postings of those who visited Yeonnam-dong from June 2013 to May 2017, divided into four periods -from June 2013 to May 2014, from June 2014 to May 2015, from June 2015 to May 2016 and from June 2016 to May 2017. The keywords used were 'Yeonnam-dong', 'Gyeongui Line' and 'Yeontral Park' and the data was further refined and resampled. A semantic network analysis was conducted on the basis of the co-occurrences of words. The results of the study were as follows. During the entire period, the main experience of visitors to Yeonnam-dong was 'food culture' consistently, but the activities related to 'market', 'browsing', and 'buy' increased. Also, activities such as 'walk', 'play' and 'rest' in the park newly appeared after the construction of the park. Moreover, more diverse opinions about the Yeonnam-dong were expressed on the blog, and Yeonnam-dong began to be recognized as a place where a variety of activities can be enjoyed. Lastly, when the visitors wrote about the theme 'food culture', the scope of the keywords expanded from simple ones, such as 'eat', 'photograph' and 'chatting' to 'market', 'browsing', and 'walk'. The sub-themes that appeared with the park also expanded to various topics with the emergence of the Gyeongui Line Book Street. This study analyzed the change of experiences of visitors objectively with text mining, a quantitative methodology. Due to the nature of text mining, however, the subjective opinions inevitably have been involved in the process of refining. Also, further research is required to assess the direct relationship between these changes and park construction.