• Title/Summary/Keyword: Date Mining

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Sentiment Analysis Main Tasks and Applications: A Survey

  • Tedmori, Sara;Awajan, Arafat
    • Journal of Information Processing Systems
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    • v.15 no.3
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    • pp.500-519
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    • 2019
  • The blooming of social media has simulated interest in sentiment analysis. Sentiment analysis aims to determine from a specific piece of content the overall attitude of its author in relation to a specific item, product, brand, or service. In sentiment analysis, the focus is on the subjective sentences. Hence, in order to discover and extract the subjective information from a given text, researchers have applied various methods in computational linguistics, natural language processing, and text analysis. The aim of this paper is to provide an in-depth up-to-date study of the sentiment analysis algorithms in order to familiarize with other works done in the subject. The paper focuses on the main tasks and applications of sentiment analysis. State-of-the-art algorithms, methodologies and techniques have been categorized and summarized to facilitate future research in this field.

Shared Spatio-temporal Attention Convolution Optimization Network for Traffic Prediction

  • Pengcheng, Li;Changjiu, Ke;Hongyu, Tu;Houbing, Zhang;Xu, Zhang
    • Journal of Information Processing Systems
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    • v.19 no.1
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    • pp.130-138
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    • 2023
  • The traffic flow in an urban area is affected by the date, weather, and regional traffic flow. The existing methods are weak to model the dynamic road network features, which results in inadequate long-term prediction performance. To solve the problems regarding insufficient capacity for dynamic modeling of road network structures and insufficient mining of dynamic spatio-temporal features. In this study, we propose a novel traffic flow prediction framework called shared spatio-temporal attention convolution optimization network (SSTACON). The shared spatio-temporal attention convolution layer shares a spatio-temporal attention structure, that is designed to extract dynamic spatio-temporal features from historical traffic conditions. Subsequently, the graph optimization module is used to model the dynamic road network structure. The experimental evaluation conducted on two datasets shows that the proposed method outperforms state-of-the-art methods at all time intervals.

Classified Recommendation Service of Date Course using Data Mining (데이터 마이닝을 이용한 맞춤형 데이트 코스 추천 서비스)

  • Song, Woo-Yong;Kim, Won-Young;kim, Ung-Mo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2009.11a
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    • pp.751-752
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    • 2009
  • 컴퓨터와 통신의 급속한 성장은 방대한 양의 정보를 서로 공유하는 정보화 시대를 출현 시켰고 이러한 많은 양의 다양한 정보로부터 유용한 정보를 얻어 내는 데이터 마이닝이라는 기법이 도입되었다. 데이터 마이닝 기법은 사회 모든 분야에 걸쳐서 사용되고 있으며 이러한 기법으로 산출된 새로운 정보는 각 분야의 의사결정을 하는데 있어서 중요한 요소로 자리 잡고 있다. 본 논문에서는 데이터 마이닝을 통하여 여가 생활의 하나인 데이트를 보다 의미 있는 시간으로 만들기 위한 개인별 맞춤형 데이트 코스 추천 서비스를 제안하고자 한다. 이를 통하여 개개인의 정보를 얻기 위한 시간과 노력을 절약하고 개인의 취향과 환경적인 요소를 고려한 특화된 서비스를 제공한다.

Non face-to-face News Articles Keyword Using Topic Modeling (토픽모델링을 이용한 비대면 신문 기사 키워드 분석)

  • Shin, Ari;Hwangbo, Jun Kwon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.11
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    • pp.1751-1754
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    • 2022
  • The news articles collected with keyword "non face-to-face" were analyzed through topic modeling applied with LDA algorithm. In this study, collected articles were divided into two periods, period 1(the beginning of COVID-19 spread) and period 2(the end of COVID-19 spread), according to issued date of the articles. The articles of period 1 showed support for non-face-to-face treatment, smart library, the beginning of the online financial era, non-face-to-face entrance exam and employment, stock investment for main topic words. And the articles of period 2 showed conversion to non face-to-face classes, increasing unmanned stores, online finance, education industry, home treatment for main topic words. Also, further issues were discussed through visualization of topic words. These results provide evidence that education and unmanned business in non-face-to-face industries are growing.

Review on Quantitative Measures of Robustness for Building Structures Against Disproportionate Collapse

  • Jiang, Jian;Zhang, Qijie;Li, Liulian;Chen, Wei;Ye, Jihong;Li, Guo-Qiang
    • International Journal of High-Rise Buildings
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    • v.9 no.2
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    • pp.127-154
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    • 2020
  • Disproportionate collapse triggered by local structural failure may cause huge casualties and economic losses, being one of the most critical civil engineering incidents. It is generally recognized that ensuring robustness of a structure, defined as its insensitivity to local failure, is the most acceptable and effective method to arrest disproportionate collapse. To date, the concept of robustness in its definition and quantification is still an issue of controversy. This paper presents a detailed review on about 50 quantitative measures of robustness for building structures, being classified into structural attribute-based and structural performance-based measures (deterministic and probabilistic). The definition of robustness is first described and distinguished from that of collapse resistance, vulnerability and redundancy. The review shows that deterministic measures predominate in quantifying structural robustness by comparing the structural responses of an intact and damaged structure. The attribute-based measures based on structural topology and stiffness are only applicable to elastic state of simple structural forms while the probabilistic measures receive growing interest by accounting for uncertainties in abnormal events, local failure, structural system and failure-induced consequences, which can be used for decision-making tools. There is still a lack of generalized quantifications of robustness, which should be derived based on the definition and design objectives and on the response of a structure to local damage as well as the associated consequences of collapse. Critical issues and recommendations for future design and research on quantification of robustness are provided from the views of column removal scenarios, types of structures, regularity of structural layouts, collapse modes, numerical methods, multiple hazards, degrees of robustness, partial damage of components, acceptable design criteria.

Analysis of Research Trends in Relation to the Yellow Sea using Text Mining (텍스트 마이닝을 활용한 황해 관련 연구동향 분석연구)

  • Kyu Won Hwang;Kim Jinkyung;Kang Seung-Koo;Kang Gil Mo
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.7
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    • pp.724-739
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    • 2023
  • Located in the sea area between South Korea, North Korea, and China, the Yellow Sea plays an important role from a geopolitical perspective, and recently, as the use of marine space in the Yellow Sea is expanding, its social and economic values have been increasing further. In addition, owing to rapid climate changes, the need for joint response and cooperation between Korea and China is increasing in various fields, including changes in the marine environment and marine ecosystem and generation and movement of air pollutants. Accordingly, in this study, core topics were derived from research papers with the Yellow Sea as a keyword, and research trends to date were explored through author network analysis. As a specific research method, research papers related to the Yellow Sea published between 1984 and 2021 were extracted from the Web of Science database and were classified into four periods to derive core topics using topic modeling, a type of text mining. Furthermore, the influences of major research communities, researchers, and research institutes in the appropriate fields were identified through analyzing the author network, and their implications were presented. The analysis results indicated that the core topics of research papers on the Yellow Sea had changed over time, and differences existed in the influence (centrality) of key researchers. Finally, based on the results of this study, this study aims to identify research trends related to the Yellow Sea, major researchers, and research institutes and contribute to research cooperation between Korea and China regarding the Yellow Sea in the future.

Research on the Movie Reviews Regarded as Unsuccessful in Box Office Outcomes in Korea: Based on Big Data Posted on Naver Movie Portal

  • Jeon, Ho-Seong
    • Asia-Pacific Journal of Business
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    • v.12 no.3
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    • pp.51-69
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    • 2021
  • Purpose - Based on literature studies of movie reviews and movie ratings, this study raised two research questions on the contents of online word of mouth and the number of movie screens as mediator variables. Research question 1 wanted to figure out which topics of word groups had a positive or negative impact on movie ratings. Research question 2 tried to identify the role of the number of movie screens between movie ratings and box office outcomes. Design/methodology/approach - Through R program, this study collected about 82,000 movie reviews and movie ratings posted on Naver's movie website to examine the role of online word of mouths and movie screen counts in 10 movies that were considered commercially unsuccessful with fewer than 2 million viewers despite securing about 1,000 movie screens. To confirm research question 1, topic modeling, a text mining technique, was conducted on movie reviews. In addition, this study linked the movie ratings posted on Naver with information of KOBIS by date, to identify the research question 2. Findings - Through topic modeling, 5 topics were identified. Topics found in this study were largely organized into two groups, the content of the movie (topic 1, 2, 3) and the evaluation of the movie (topics 4, 5). When analyzing the relationship between movie reviews and movie ratings with 5 mediators identified in topic modeling to probe research question 1, the topic word groups related to topic 2, 3 and 5 appeared having a negative effect on the netizen's movie ratings. In addition, by connecting two secondary data by date, analysis for research question 2 was implemented. The outcomes showed that the causal relationship between movie ratings and audience numbers was mediated by the number of movie screens. Research implications or Originality - The results suggested that the information presented in text format was harder to quantify than the information provided in scores, but if content information could be digitalized through text mining techniques, it could become variable and be analyzed to identify causality with other variables. The outcomes in research question 2 showed that movie ratings had a direct impact on the number of viewers, but also had indirect effects through changes in the number of movie screens. An interesting point is that the direct effect of movie ratings on the number of viewers is found in most American films released in Korea.

Outdoor Healing Places Perception Analysis Using Named Entity Recognition of Social Media Big Data (소셜미디어 빅데이터의 개체명 인식을 활용한 옥외 힐링 장소 인식 분석)

  • Sung, Junghan;Lee, Kyungjin
    • Journal of the Korean Institute of Landscape Architecture
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    • v.50 no.5
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    • pp.90-102
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    • 2022
  • In recent years, as interest in healing increases, outdoor spaces with the concept of healing have been created. For more professional and in-depth planning and design, the perception and characteristics of outdoor healing places through social media posts were analyzed using NER. Text mining was conducted using 88,155 blog posts, and frequency analysis and clique cohesion analysis were conducted. Six elements were derived through a literature review, and two elements were added to analyze the perception and the characteristics of healing places. As a result, visitors considered place elements, date and time, social elements, and activity elements more important than personnel, psychological elements, plants and color, and form and shape when visiting healing places. The analysis allowed the derivation of perceptions and characteristics of healing places through keywords. From the results of the Clique, keywords, such as places, date and time, and relationship, were clustered, so it was possible to know where, when, what time, and with whom people were visiting places for healing. Through the study, the perception and characteristics of healing places were derived by analyzing large-scale data written by visitors. It was confirmed that specific elements could be used in planning and marketing.

Research and Development Trends for Mine Subsidence Prevention Technology in Korea (한국의 광산 지반침하방지기술 연구개발 동향)

  • Kim, Soo Lo;Park, Joo Hyun
    • Tunnel and Underground Space
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    • v.25 no.5
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    • pp.408-416
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    • 2015
  • The collapse of the underground cavities and voids, which were made for developing mineral resources, can cause the subsidence of the ground surface in the residential areas. During the Japanese colonial era and the 1960's mining boom period, lots of mines had been developed indiscriminately in Korea. Due to complicated geological conditions and mining methods, many of dangerous underground mine cavities with steep slopes had been generated at the shallow surface. Due to such conditions, it is difficult to directly apply valid foreign reclamation practice for the cavities in Korea environments. It is necessary to develop the efficient ground stabilization technologies for the Korea underground mine conditions to solve abandoned mine reclamation properly. Therefore, MIRECO and Korea government have been carrying out practical researches and technical developments together with other academic researchers and reclamation business partners, and various practical solutions such as surveying and exploration methods, proper cavity filling materials and reinforcement methods have been developed with application in the mine field. In this article, up to date technologies and R&D trends in the field of mine subsidence prevention technology are broadly reviewed to establish the future direction of a research and development.

A Patent Trend Analysis for Technological Convergence of IoT and Wearables (IoT와 Wearables 기술융합을 위한 특허동향분석)

  • Kang, Ji Ho;Kim, Jong Chan;Lee, Jun Hyuck;Park, Sang Sung;Jang, Dong Sik
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.3
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    • pp.306-311
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    • 2015
  • This study aims at analyzing the convergence of Internet-of-Things and wearables technologies using cooperative patent classification(CPC). CPC, introduced to an increasing number of technological fields of Korean patents, is expected to be widely used in Patent Informatics because the classification codes in CPC are more specific than those of IPC, which reflect the characteristics of technologies in detail with accuracy. CPC has seldom been used up to date and most of the previous researches on technological convergence used IPC. As a pre-analysis step for analyzing the trend of technological convergence of IoT and wearables, CPC and IPC codes assigned to each patent were compared. By applying association rule mining to the analysis of CPC codes, we identified the technological fields where convergence frequently takes place and examined the trend of technological convergence over time.