• Title/Summary/Keyword: Medical blog

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A Classification of Medical and Advertising Blogs Using Machine Learning (머신러닝을 이용한 의료 및 광고 블로그 분류)

  • Lee, Gi-Sung;Lee, Jong-Chan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.11
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    • pp.730-737
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    • 2018
  • With the increasing number of health consumers aiming for a happy quality of life, the O2O medical marketing market is activated by choosing reliable health care facilities and receiving high quality medical services based on the medical information distributed on web's blog. Because unstructured text data used on the Internet, mobile, and social networks directly or indirectly reflects authors' interests, preferences, and expectations in addition to their expertise, it is difficult to guarantee credibility of medical information. In this study, we propose a blog reading system that provides users with a higher quality medical information service by classifying medical information blogs (medical blog, ad blog) using bigdata and MLP processing. We collect and analyze many domestic medical information blogs on the Internet based on the proposed big data and machine learning technology, and develop a personalized health information recommendation system for each disease. It is expected that the user will be able to maintain his / her health condition by continuously checking his / her health problems and taking the most appropriate measures.

Web based PBL Teaching·Learning Development Model for Medical Education (의료정보 교육을 위한 웹기반 PBL 교수·학습 콘텐츠 개발 모형)

  • Choo, Hyun-Jae;Park, Joo-Hee
    • The Journal of the Korea Contents Association
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    • v.10 no.10
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    • pp.246-254
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    • 2010
  • Recent changes in medical environment are based on technology such as internet. As most hospitals require the change and the adaptation of medical, medical information experts are more needed. In this study, we developed web based PBL model and applied it to the students majoring in medical information system. The developed web-PBL model focuses on learner's online learning activities to enhance collaborative learning and self-directed learning by using online learning tools. At the result of the research, We found that the students' course evaluation somewhat increased compared to the previous class and the students positively perceived on PBL model. Moreover, this study showed that using blog as a online learning tool was a good way to enhance cooperative learning.

Funology Body : Classified Application System Based on Funology and Philosophy of the Human Body (Funology Body : Funology와 '몸의 철학' 이론을 바탕으로 한 어플리케이션 분류 검색 체계 연구)

  • Kihl, Tae-Suk;Jang, Ju-No;Ju, Hyun-Sun;Kwon, Ji-Eun
    • Science of Emotion and Sensibility
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    • v.13 no.4
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    • pp.635-646
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    • 2010
  • This article focuses on Funology and a new classified application system based on concept of language and thought which are formed by body experience. It is defined by Funology Body as that. Funology Body is classifying and searching system which are consisted of a body, world (environment), and device tool. The body is sectioned by Brain, Eyes, Ears, Nose, Mouth, Hand, Torso, Feet, and Heart according as parts of the human body. This allows intuiting and experience searching as making classified system connected to the application relationship with concept of an each part of body. The Brain of the body is sub-classified by Book, Account, Business, Memory, Education, Search, and Aphorism to imply the application with thought. The Eyes take Video, Photography, and Broadcast for visibility. The Ears is categorized as Music, Instrument, Audio, and Radio for hearing. The Nose gets Perfume, Smell for olfactory sense. The Mouth is sectioned by Food, SNS, Chatting, Email, and Blog for eating and communication. The Hand sorts into Games, Kits, and Editing to handle, create, and play. The Torso is grouped by Health, Medical, Dance, Sport, Fashion, and Testyuorself related by protecting internal and meaning of the body core. The Feet is classified by Travel, Transportation, Map, and Outdoor for moving and concept of expanding the terrain. The Heart is consisted of Fear, Anger, Joy, Sadness, Acceptance, Disgust, Expectation, and Surprise for a human feeling. Beyond that, the World takes News, Time, Weather, Map, Fortune, and Shop, and Device tool gets Interface, Utilities. The Funology Body has a unique characteristic of giving intuitive and sensuous pleasure and reflection of users' attitude and taste for changing application flexibly.

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Design And Implementation of a Speech Recognition Interview Model based-on Opinion Mining Algorithm (오피니언 마이닝 알고리즘 기반 음성인식 인터뷰 모델의 설계 및 구현)

  • Kim, Kyu-Ho;Kim, Hee-Min;Lee, Ki-Young;Lim, Myung-Jae;Kim, Jeong-Lae
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.12 no.1
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    • pp.225-230
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    • 2012
  • The opinion mining is that to use the existing data mining technology also uploaded blog to web, to use product comment, the opinion mining can extract the author's opinion therefore it not judge text's subject, only judge subject's emotion. In this paper, published opinion mining algorithms and the text using speech recognition API for non-voice data to judge the emotions suggested. The system is open and the Subject associated with Google Voice Recognition API sunwihwa algorithm, the algorithm determines the polarity through improved design, based on this interview, speech recognition, which implements the model.

Analysis of Major COVID-19 Issues Using Unstructured Big Data (비정형 빅데이터를 이용한 COVID-19 주요 이슈 분석)

  • Kim, Jinsol;Shin, Donghoon;Kim, Heewoong
    • Knowledge Management Research
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    • v.22 no.2
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    • pp.145-165
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    • 2021
  • As of late December 2019, the spread of COVID-19 pandemic began which put the entire world in panic. In order to overcome the crisis and minimize any subsequent damage, the government as well as its affiliated institutions must maximize effects of pre-existing policy support and introduce a holistic response plan that can reflect this changing situation- which is why it is crucial to analyze social topics and people's interests. This study investigates people's major thoughts, attitudes and topics surrounding COVID-19 pandemic through the use of social media and big data. In order to collect public opinion, this study segmented time period according to government countermeasures. All data were collected through NAVER blog from 31 December 2019 to 12 December 2020. This research applied TF-IDF keyword extraction and LDA topic modeling as text-mining techniques. As a result, eight major issues related to COVID-19 have been derived, and based on these keywords, this research presented policy strategies. The significance of this study is that it provides a baseline data for Korean government authorities in providing appropriate countermeasures that can satisfy needs of people in the midst of COVID-19 pandemic.

Issues of Applying Intelligent RSS Framework to Electronic Commerce (전자상거래의 지능형 RSS 도입을 위한 이슈 분석과 지능형 RSS 프레임워크의 제안)

  • Park, Sang-Un;Kang, Ju-Young;Kim, Woo-Ju
    • The Journal of Society for e-Business Studies
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    • v.12 no.2
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    • pp.269-290
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    • 2007
  • RSS is a core component of Web 2.0 which is expected to lead the most important innovation in the new IT environment. In that sense, it is actively utilized to distribute Web contents in various areas such as news, blog, multimedia, medical information, and conference and journal information. Also, it is expected to be a major effective marketing tool in electronic commerce domain. In the paper, we analyzed the problems of current utilization of RSS in domestic shopping malls, and suggest requirements for the effective use of RSS in electronic commerce. Furthermore, we proposed various issues and answers on the implementation of the requirements, and designed the intelligent RSS framework for electronic commerce based on the issues. Syntactic and semantic interoperability between the RSS service provider and the user is one of the most important issues in the framework. We suggested how to implement the interoperability based on Semantic Web technologies.

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Classifying and Characterizing the Types of Gentrified Commercial Districts Based on Sense of Place Using Big Data: Focusing on 14 Districts in Seoul (빅데이터를 활용한 젠트리피케이션 상권의 장소성 분류와 특성 분석 -서울시 14개 주요상권을 중심으로-)

  • Young-Jae Kim;In Kwon Park
    • Journal of the Korean Regional Science Association
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    • v.39 no.1
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    • pp.3-20
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    • 2023
  • This study aims to categorize the 14 major gentrified commercial areas of Seoul and analyze their characteristics based on their sense of place. To achieve this, we conducted hierarchical cluster analysis using text data collected from Naver Blog. We divided the districts into two dimensions: "experience" and "feature" and analyzed their characteristics using LDA (Latent Dirichlet Allocation) of the text data and statistical data collected from Seoul Open Data Square. As a result, we classified the commercial districts of Seoul into 5 categories: 'theater district,' 'traditional cultural district,' 'female-beauty district,' 'exclusive restaurant and medical district,' and 'trend-leading district.' The findings of this study are expected to provide valuable insights for policy-makers to develop more efficient and suitable commercial policies.

Korean Customer Attitudes Towards SNS Shopping

  • Cho, Young-Sang;Heo, Jeong-Yoon;Youn, Myoung-Kil
    • Journal of Distribution Science
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    • v.10 no.8
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    • pp.7-14
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    • 2012
  • As a new format of retailing, social shopping on SNS has rapidly grown in recent. Although there is much literature associated with customer behaviours in the academic world, little attention has been paid to identifying the shopping patterns of SNS shoppers. This paper will, thus, identify how perceived value has an impact on the buying intention of SNS shoppers, after illustrating what kind of factor influences the formation process of perceived value in the Korean marketplace. Given that SNS shoppers are for the most part 20s as well as 30s, the authors handed out questionnaires to them. Furthermore, based on literature review results, the conceptualised research model was developed. Despite lack of literature, the authors developed five constructs like price reduction, quantity- and time-limited message, product ranges, information-sharing, and required number of shoppers. The researchers made a considerable effort to identify the relationship between research concepts and each variable, based on a few research analysis methods such as frequency analysis, the Varimax rotation technique used orthogonal rotation, Cronbach's Alpha, PCA (Principle Component Analysis), and the like. Amongst the 5 variables used to measure the degree of influences on the perceived value as a social shopping characteristic, it has been evident that price cut, required minimum shoppers, product variety, and information-sharing have a positive impact on the perceived value formation processes of SNS customers. Also, this research implies that SNS retailers can differentiate themselves from other retailers by differently using the above factors. From a practitioner's point of view, these factors should be strategically used to increase the social shopping opportunities of SNS users. It is, furthermore, evident that the perceived value formed by the above 4 factors have played an important role in the buying decision process of SNS customers. In a sense, whether customers are aware of higher price cut rates, information-sharing, required minimum shoppers, and product variety has a positive impact on making buying decisions. From a retailer's point of view, online shopping mall operators are able to use blog as well as twitter to improve the buying intention as a marketing tool of social network, because the business activities provided by social shopping retailers, like the rapid, accurate responses to customer requirements, the provision of a variety of information, and the communications between customers are closely related to buying intentions. There are a few research limitations to conduct this empirical research. It was not easy to review prior papers, due to its lack. In spite of the increasing number of SNS shoppers in Korea, little research attention has been paid to this kind of research topic by academicians, because buying products or services through SNS is in its infancy. With regard to research populations, it would be difficult to generalise the research findings in Korea, owing to unbalanced respondent distribution. Considering the above research limitations as well as the growth of social shopping, many authors should pay considerable attention to SNS-related issues in the future, and develop the more sophisticated criteria to measure the characteristics of SNS shoppers.

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The Analysis of Public Awareness about Literary Therapy by Utilizing Big Data Analysis - The aspects of convergence literature and statistics (빅데이터 분석을 통한 문학치료의 대중적 인지도 분석 - 국문학과 통계학의 융합적 측면)

  • Choi, Kyoung-Ho;Park, Jeong-Hye
    • Journal of Digital Convergence
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    • v.13 no.4
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    • pp.395-404
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    • 2015
  • This study is exploring objective awareness of literary therapy by consideration of popular perception about literary therapy through analysis of big data. The purpose of this study is the deduction of meaning information through analysis in the viewpoint of big data at online social network service(SNS) about 'literary therapy'. Accordingly, the main way of research became content analysis of keyword linked to literary therapy by utilizing opinion mining method related to text mining. The study mainly grasped 'literary therapy' and analyzed 'bibliotherapy' comparatively. The period of study was from Oct. 10th to Nov. 10th, 2014(during 30 days), and SNS such as blog or twitter became the subject of search. Through the result of study analysis, the conclusion that the spread of literary therapeutic prospect, structural harmony of literary therapeutic field, and the solidity of perceptional axis about literary therapy are needed can be drawn. This study is worthwhile because it can investigate popular awareness about literary therapy and can suggest alternative for invigoration of literary therapy.