• Journal of Intelligence and Information Systems
• /
• v.15 no.2
• /
• pp.61-74
• /
• 2009

With an exponential growth of blogs, lots of important data have appeared on blogs. However, since main topics mentioned in blog pages are quite different from general web pages, there are problems which can't be solved by general search engines. Therefore, many researchers have studied searching methods only for blogs to help users who want to have useful information on blog. We also present a blog classifying method based on similarity of titles. First, we analyze blogs and blog search engines to find problems and solution of current blog search. Second, applying our similarity algorithm on blog titles, we discuss a way to develop clustering method only for blog. Finally, by making a prototype system of our algorithm, we evaluate our algorithm's effectiveness and show conclusion and future work. We expect this algorithm could add its power to current search engine.

• Journal of Intelligence and Information Systems
• /
• v.22 no.1
• /
• pp.187-204
• /
• 2016

Document classification based on emotional polarity has become a welcomed emerging task owing to the great explosion of data on the Web. In the big data age, there are too many information sources to refer to when making decisions. For example, when considering travel to a city, a person may search reviews from a search engine such as Google or social networking services (SNSs) such as blogs, Twitter, and Facebook. The emotional polarity of positive and negative reviews helps a user decide on whether or not to make a trip. Sentiment analysis of customer reviews has become an important research topic as datamining technology is widely accepted for text mining of the Web. Sentiment analysis has been used to classify documents through machine learning techniques, such as the decision tree, neural networks, and support vector machines (SVMs). is used to determine the attitude, position, and sensibility of people who write articles about various topics that are published on the Web. Regardless of the polarity of customer reviews, emotional reviews are very helpful materials for analyzing the opinions of customers through their reviews. Sentiment analysis helps with understanding what customers really want instantly through the help of automated text mining techniques. Sensitivity analysis utilizes text mining techniques on text on the Web to extract subjective information in the text for text analysis. Sensitivity analysis is utilized to determine the attitudes or positions of the person who wrote the article and presented their opinion about a particular topic. In this study, we developed a model that selects a hot topic from user posts at China's online stock forum by using the k-means algorithm and self-organizing map (SOM). In addition, we developed a detecting model to predict a hot topic by using machine learning techniques such as logit, the decision tree, and SVM. We employed sensitivity analysis to develop our model for the selection and detection of hot topics from China's online stock forum. The sensitivity analysis calculates a sentimental value from a document based on contrast and classification according to the polarity sentimental dictionary (positive or negative). The online stock forum was an attractive site because of its information about stock investment. Users post numerous texts about stock movement by analyzing the market according to government policy announcements, market reports, reports from research institutes on the economy, and even rumors. We divided the online forum's topics into 21 categories to utilize sentiment analysis. One hundred forty-four topics were selected among 21 categories at online forums about stock. The posts were crawled to build a positive and negative text database. We ultimately obtained 21,141 posts on 88 topics by preprocessing the text from March 2013 to February 2015. The interest index was defined to select the hot topics, and the k-means algorithm and SOM presented equivalent results with this data. We developed a decision tree model to detect hot topics with three algorithms: CHAID, CART, and C4.5. The results of CHAID were subpar compared to the others. We also employed SVM to detect the hot topics from negative data. The SVM models were trained with the radial basis function (RBF) kernel function by a grid search to detect the hot topics. The detection of hot topics by using sentiment analysis provides the latest trends and hot topics in the stock forum for investors so that they no longer need to search the vast amounts of information on the Web. Our proposed model is also helpful to rapidly determine customers' signals or attitudes towards government policy and firms' products and services.

• Journal of Society of Occupational Therapy for the Aged and Dementia
• /
• v.12 no.2
• /
• pp.67-74
• /
• 2018

Objective : The purpose of this study is to quantitatively analyze the role of occupational therapy in long - term care insurance for the elderly using text mining, one of the big data analysis techniques. Method : For the analysis of newspaper articles, "Long - Term Care Insurance for the Elderly + Occupational Therapy for the Elderly" was collected after the period from 2007 to 208. Naver, which has a high share of the domestic search engine, utilized the database of Naver News by utilizing Textom, a web crawling tool. After collecting the article title and original text of 510 news data from the collection of the elderly long term care insurance + occupational therapy search, we analyzed the article frequency and key words by year. Result : In terms of the frequency of articles published by year, the number of articles published in 2015 and 2017 was the highest with 70 articles (13.7%), and the top 10 terms of the key word analysis showed the highest frequency of 'dementia' (344) In terms of key words, dementia, treatment, hospital, health, service, rehabilitation, facilities, institution, grade, elderly, professional, salary, industrial complex and people are related. Conclusion : In this study, it is meaningful that the textual mining technique was used to more objectively confirm the social needs and the role of the occupational therapist for the dementia and rehabilitation in the related key keywords based on the media reporting trend of the elderly long - term care insurance for 11 years. Based on the results of this study, future research should expand research field and period and supplement the research methodology through various analysis methods according to the year.

• International Commerce and Information Review
• /
• v.15 no.2
• /
• pp.387-410
• /
• 2013

The competition aspect of business has been transformed from competition among companies to competition among ecosystem, and has been grown to platform based business, which is defined as ecosystem among business. Coming to the spotlight with the advantages of platform business combined software and hardware like Apple, platform business have been emerging in many fields. In this research, we define platform and platform based business, and then review related researches. After this, we review four representative research methodologies which are Yin(2011)' s case analysis research, Eisenhardt(2007)' s case analysis research, Romano etc' s web based qualitative data analysis method(2003), and Creswll(2010)' s open coding technique. And then, we suggest this research' s natural methodology combined with the advantages of four research methodologies. Based on our research methodology, we choose three high commercialized categories, which are smartphone platform business, social platform business, and search engine platform business. And then, we choose seven companies in three categories with success cases & failure cases, and analysis each case in perspective of our research methodology. And then, we suggest critical success & failure elements. Based on our findings, we suggest three strategic elements for the longevity of platform based business. Finally, we suggest the limitations of our research and further research issues.

• Journal of KIISE:Databases
• /
• v.37 no.5
• /
• pp.258-266
• /
• 2010

In this paper, we introduce a novel method to predict next update of blogs. The number of RSS feeds registered on meta-blogs is on the order of several million. Checking for updates is very time consuming and imposes a heavy burden on network resources. Since blog search engine has limited resources, there is a fix number of blogs that it can visit on a day. Nevertheless we need to maximize chances of getting new data, and the proposed method which predicts update probability on blogs could bring better chances for it. Also this work is important to avoid distributed denial-of-service attack for the owners of blogs. Furthermore, for the internet as whole this work is important, too, because our approach could minimize traffic. In this study, we assumed that there is a specific pattern to when a blogger is actively posting, in terms of days of the week and, more specifically, hours of the day. We analyzed 15,119 blogs to determine a blogger's posting preference. This paper proposes a method to predict the update probability based on a blogger's posting history and preferred days of the week. We applied proposed method to 12,115 blogs to check the precision of our predictions. The evaluation shows that the model has a precision of 0.5 for over 93.06% of the blogs examined.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.7
• /
• pp.475-486
• /
• 2020

The purpose of present study is to identify the regional tourism resources using Webometric network analysis. The study focuses on Suseong area in Daegu metropolitan city. Various kinds of web-based data, for example, hit counts, online news, and public comments, were used to discover hot places and people's responses. The research question is, 'First, what is the optimum level of the search engine for suseong? Second, what is the online appearance of tourist resources in suseong? Which region is the center of tourism with high levels of emergence? Third, what are the main contents of news articles and comments related to the Suseong pond?'. The results show that the search engine optimization level in Suseong is lower than that in other areas in Daegu. In other words, tourism information and contents regarding Suseong are not highly visible on cyber space. Importantly, Suseong pond had the highest online presence. A close analysis of both online news and users' comments on Suseong pond, however, revealed the biggest concern as calling for improving public accessibility to tourism infrastructure. The findings are expected to contribute to policy development and service operation related to tourism resources in Suseong.

• Science of Emotion and Sensibility
• /
• v.21 no.4
• /
• pp.43-54
• /
• 2018

The aim of this study is to determine the effect of motion sickness on pupil rhythm. Sixteen volunteers of both genders (8 male, 8 female, mean age $25.67{\pm}2.43$ years) experienced VR contents in both 2D and HMD versions for 15 minutes, and their pupillary rhythms were compared. The irregular pattern of the pupillary rhythms, as demonstrated by increasing mean pupil diameter (mPD) and standard deviation of the pupil diameter (sPD), revealed motion sickness after experiencing HMD condition. The pupillary response is strongly related to the cognitive load, and the motion sickness can be interpreted as a change in the cognitive load caused by the increasing volume of visual information that must be processed and the conflict or inconsistency between different sensory modalities. The method proposed in this study could be a non-contact measurement method for the monitoring of motion sickness using a web-camera rather than previous sensor-based methods.

• Archives of design research
• /
• v.18 no.2 s.60
• /
• pp.5-14
• /
• 2005

Graphic Design is being developed as a unique genre and widely applied to movie, TV broadcasting, music video, computer an, web design, animation, and game. Some university added motion graphics in their curriculum recently. However Motion Graphic has not been defined clearly and pedagogy of motion graphics was not studied enough. Motion Graphic is not merely moving picture. Its typical purpose and concept are evolving because of the diversified application. Meta-synthesis between media and hybrid development based on diverse approach and composite presentational methods are also changing Motion Graphic. Various technology such as photograph, analytical engine, hypermedia, multimedia, digital composite picture, network and interface should be studied to understand Motion Graphic. This study reviews the historic background of Motion Graphic mainly related to its advent. A fundamental definition of Motion Graphic including the space and time is suggested and the international trend is introduced. Future Motion Graphic and possible development was also predicted.

• Journal of Korea Multimedia Society
• /
• v.12 no.10
• /
• pp.1499-1507
• /
• 2009

With the abundance of digital contents, the necessity of precise indexing technology is consistently required. To meet these requirements, the intelligent software entity needs to be the subject of information retrieval and the interoperability among intelligent entities including human must be supported. In this paper, we analyze the unifying framework for multi-modality indexing that Snoek and Worring proposed. Our work investigates the method of improving the authenticity of indexing information in contents-based automated indexing techniques. It supports the creation and control of abstracted high-level indexing information through ontological concepts of Semantic Web skills. Moreover, it attempts to present the fundamental model that allows interoperability between human and machine and between machine and machine. The memory-residence model of processing ontology is inappropriate in order to take-in an enormous amount of indexing information. The use of ontology repository and inference engine is required for consistent retrieval and reasoning of logically expressed knowledge. Our work presents an experiment for storing and retrieving the designed knowledge by using the Minerva ontology repository, which demonstrates satisfied techniques and efficient requirements. At last, the efficient indexing possibility with related research is also considered.

• Archives of design research
• /
• v.17 no.4
• /
• pp.79-88
• /
• 2004

This study is aimed to grasp the organization of Internet information resources and to infer the characteristics of resource search engines so that criteria may be established to classify and evaluate Internet information resources. In addition, the author has compared and analyzed interior design classification systems of directory sites of each subject that provide classification system based on the Internet, foreign sites to be used to search for information, and domestic information-specialized sites in order to set up models of interior design classification systems of directories of each Web subject. The systems have been analyzed against such four measures as comprehensiveness of the subject scope, logicality of classification systems, preciseness of subject terms, and effectiveness of searches. Information of interior designs is mixed with that of related fields, and so its information search and classification are not organized systematically. The author has analyzed such a problem so as to present models of search engine classification systems for interior design information classification after considering both academic and practical aspects.