• Title/Summary/Keyword: Visualization Method

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A Study of 'Emotion Trigger' by Text Mining Techniques (텍스트 마이닝을 이용한 감정 유발 요인 'Emotion Trigger'에 관한 연구)

  • An, Juyoung;Bae, Junghwan;Han, Namgi;Song, Min
    • Journal of Intelligence and Information Systems
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    • v.21 no.2
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    • pp.69-92
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    • 2015
  • The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

Construction and Application of Intelligent Decision Support System through Defense Ontology - Application example of Air Force Logistics Situation Management System (국방 온톨로지를 통한 지능형 의사결정지원시스템 구축 및 활용 - 공군 군수상황관리체계 적용 사례)

  • Jo, Wongi;Kim, Hak-Jin
    • Journal of Intelligence and Information Systems
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    • v.25 no.2
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    • pp.77-97
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    • 2019
  • The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

A Proposal of a Keyword Extraction System for Detecting Social Issues (사회문제 해결형 기술수요 발굴을 위한 키워드 추출 시스템 제안)

  • Jeong, Dami;Kim, Jaeseok;Kim, Gi-Nam;Heo, Jong-Uk;On, Byung-Won;Kang, Mijung
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.1-23
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    • 2013
  • To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

A Study of Visualization and Analysis Method about Plants Social Network Used for Planting Design - Focusing on Forest Vegetation Area in Busan Metropolitan City - (식재설계에 활용 가능한 식물사회네트워크 시각화 및 분석 방법에 관한 연구 - 부산광역시 산림식생지역을 중심으로 -)

  • Lee, Sang-Cheol;Choi, Song-Hyun;Cho, Woo
    • Korean Journal of Environment and Ecology
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    • v.34 no.3
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    • pp.259-270
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    • 2020
  • Plants Social Network (PSN) was first used in recent studies to incorporate the plant sociology methods for the understanding of plant society with the social network analysis methods that have recently attracted attention in the social science and visualize and analyze a PSN. The process of construction and analysis on PSN proceeds in the order of setting up the survey area, investigating the appearance plants species on plots of 100㎡, analyzing the interspecific association, building the sociogram, and analyzing the network structure and centrality. This study established a PSN by investigating the appearance species after installing 708 plots to include various dominant vegetational physiognomies in Busan Metropolitan City, where coastal and inland vegetation could be observed simultaneously. The survey found a total of 195 species, including 42 species of evergreen, 151 species of deciduous trees, and 2 species of semi-evergreen trees. The interspecies binding analysis was performed with the focus on the total number of species. It showed the number of friendly species in the order of Eurya japonica (47 species), Trachelospermum asiaticum (46 species), Linder glauca (44 species), Sorbus alnifolia (44 species), and Ligustrum japonicum (41 species). Based on it, we generated a sociogram using Gephi 0.9.2 program. The sociogram was divided into groups that appeared mostly on the coast and those that did not, reflecting the geographical distribution characteristics of forest vegetation in Busan. The analysis of the network structured showed 1,709 links and an average of 17.5 species having interspecies binding with a species. The density was 0.09, the diameter was 5, and the average path distance was 2.268. We concluded that various PSNs should be established in the future for precise comparative analysis of network characteristics in the social science field. In the PSN of Busan Metropolitan City, Eurya japonica, Linder glauca, Ligustrum japonicum, and Trachelospermum asiaticum showed high centrality.

Comparative Study on the Methodology of Motor Vehicle Emission Calculation by Using Real-Time Traffic Volume in the Kangnam-Gu (자동차 대기오염물질 산정 방법론 설정에 관한 비교 연구 (강남구의 실시간 교통량 자료를 이용하여))

  • 박성규;김신도;이영인
    • Journal of Korean Society of Transportation
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    • v.19 no.4
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    • pp.35-47
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    • 2001
  • Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence. numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristic of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a methodology of motor vehicle emission calculation by using real-time traffic data was studied. A methodology for estimating emissions of CO at a test area in Seoul. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It was calculated speed-related mass of CO emission from traffic tail pipe of data from traffic system, and parameters are considered, volume, composition, average velocity, link length. And, the result was compared with that of a method of emission calculation by VKT(Vehicle Kilometer Travelled) of vehicles of category.

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Suprapubic Bladder Aspiration Assisted by Ultrasound (초음파 보조하에 시행한 치골상부 방광천자의 유용성)

  • Lee Jung Won;Park Soeun;Cho Su Jin;Yoo Eun Sun;Kim Hae Soon;Lee Seoung Joo
    • Childhood Kidney Diseases
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    • v.6 no.1
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    • pp.68-74
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    • 2002
  • Purpose: Suprapubic bladder aspiration(SBA) of urine is the most reliable method to obtain urine avoiding contamination in non-toilet trained infants. Ultrasonography is a useful tool for guiding the anatomic location as well as for direct visualization during procedure. We evaluated the success rate and complication of ultrasound(US) assisted SBA Methods. Sixty infants who visited Ewha Womans University Mokdong Hospital, with suspected urinary tract infection were randomly divided into the US assisted (n=32) and blind SBA(control, n=28) group. In US assisted SBA group, the anteroposterior(AP), transverse, and sagittal diameters and the volume of the bladder were measured. In the blind SBA group, urine was blindly aspirated when the urinary bladder was palpated at the suprapubic area. The rate of successful urine aspiration, the number of attempts until successful aspiration, aspirated urine volume were compared between the two groups. Results: The success rate was $100\%$(32/32) in the US assisted group, which was significantly higher than $85.7\%$(24/28) of the control group (P<0.05). The aspirated urine volume in the US assisted group was $7.4{\pm}3.7\;mL$, which was significantly higher than $4.5{\pm}3.4\;mL$ of the control group (P<0.05), The diameters and volume of bladder in successful aspiration were $2.1{\pm}0.7\;cm$ in AP diameter, $3.1{\pm}0.6\;cm$ in transverse diameter, $4.2{\pm}1.0\;cm$ in sagittal diameter and $15.2{\pm}10.4\;mL$ in volume, which were significantly higher than those ($1.7{\pm}0.3\;cm,\;1.7{\pm}0.3\;cm,\;1.8{\pm}0.7\;cm,\;2.4{\pm]0.6\;cm,\;3.9{\pm}2.5$) of the control group (P<0.05) The correlations between the AP(r=0.78), transverse (r=0.72), sagittal(r=0.91) diameter and bladder volume were significant (P<0.05). SBA was $100\%$ successful in the AP diameter >3 cm, transverse diameter >4 cm, depth >4 cm and bladder volume >5 mL. Conclusion: US assistance can significantly improve the success rate of SBA in infant with suspected urinary tract infection. (J Korean Soc Pediatr Nephrol 2002 ; 6 : 68-74)

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A Destructive Method in the Connection of the Algorithm and Design in the Digital media - Centered on the Rapid Prototyping Systems of Product Design - (디지털미디어 환경(環境)에서 디자인 특성(特性)에 관한 연구(硏究) - 실내제품(室內製品) 디자인을 중심으로 -)

  • Kim Seok-Hwa
    • Journal of Science of Art and Design
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    • v.5
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    • pp.87-129
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    • 2003
  • The purpose of this thesis is to propose a new concept of design of the 21st century, on the basis of the study on the general signification of the structures and the signs of industrial product design, by examining the difference between modern and post-modern design, which is expected to lead the users to different design practice and interpretation of it. The starting point of this study is the different styles and patterns of 'Gestalt' in the post-modern design of the late 20th century from modern design - the factor of determination in industrial product design. That is to say, unlike functional and rational styles of modern product design, the late 20th century is based upon the pluralism characterized by complexity, synthetic and decorativeness. So far, most of the previous studies on design seem to have excluded visual aspects and usability, focused only on effective communication of design phenomena. These partial studies on design, blinded by phenomenal aspects, have resulted in failure to discover a principle of fundamental system. However, design varies according to the times; and the transformation of design is reflected in Design Pragnanz to constitute a new text of design. Therefore, it can be argued that Design Pragnanz serves as an essential factor under influence of the significance of text. In this thesis, therefore, I delve into analysis of the 20th century product design, in the light of Gestalt theory and Design Pragnanz, which have been functioning as the principle of the past design. For this study, I attempted to discover the fundamental elements in modern and post-modern designs, and to examine the formal structure of product design, the users' aesthetic preference and its semantics, from the integrative viewpoint. Also, with reference to history and theory of design my emphasis is more on fundamental visual phenomena than on structural analysis or process of visualization in product design, in order to examine the formal properties of modern and post-modern designs. Firstly, In Chapter 1, 'Issues and Background of the Study', I investigated the Gestalt theory and Design Pragnanz, on the premise of formal distinction between modern and post-modern designs. These theories are founded upon the discussion on visual perception of Gestalt in Germany in 1910's, in pursuit of the principle of perception centered around visual perception of human beings. In Chapter 2, I dealt with functionalism of modern design, as an advance preparation for the further study on the product design of the late 20th century. First of all, in Chapter 2-1, I examined the tendency of modern design focused on functionalism, which can be exemplified by the famous statement 'Form follows function'. Excluding all unessential elements in design - for example, decoration, this tendency has attained the position of the international style based on the spirit of Bauhause - universality and regularity - in search of geometric order, standardization and rationalization. In Chapter 2-2, I investigated the anthropological viewpoint that modern design started representing culture in a symbolic way including overall aspects of the society - politics, economics and ethics, and its criticism on functionalist design that aesthetic value is missing in exchange of excessive simplicity in style. Moreover, I examined the pluralist phenomena in post-modern design such as kitsch, eclecticism, reactionism, hi-tech and digital design, breaking away from functionalist purism of modern design. In Chapter 3, I analyzed Gestalt Pragnanz in design in a practical way, against the background of design trends. To begin with, I selected mass product design among those for the 20th century products as a target of analysis, highlighting representative styles in each category of the products. For this analysis, I adopted the theory of J. M Lehnhardt, who gradated in percentage the aesthetic and semantic levels of Pragnantz in design expression, and that of J. K. Grutter, who expressed it in a formula of M = O : C. I also employed eight units of dichotomies, according to the G. D. Birkhoff's aesthetic criteria, for the purpose of scientific classification of the degree of order and complexity in design; and I analyzed phenomenal aspects of design form represented in each unit. For Chapter 4, I executed a questionnaire about semiological phenomena of Design Pragnanz with 28 units of antonymous adjectives, based upon the research in the previous chapter. Then, I analyzed the process of signification of Design Pragnanz, founded on this research. Furthermore, the interpretation of the analysis served as an explanation to preference, through systematic analysis of Gestalt and Design Pragnanz in product design of the late 20th century. In Chapter 5, I determined the position of Design Pragnanz by integrating the analyses of Gestalt and Pragnanz in modern and post-modern designs In this process, 1 revealed the difference of each Design Pragnanz in formal respect, in order to suggest a vision of the future as a result, which will provide systemic and structural stimulation to current design.

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Patients Setup Verification Tool for RT (PSVTS) : DRR, Simulation, Portal and Digital images (방사선치료 시 환자자세 검증을 위한 분석용 도구 개발)

  • Lee Suk;Seong Jinsil;Kwon Soo I1;Chu Sung Sil;Lee Chang Geol;Suh Chang Ok
    • Radiation Oncology Journal
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    • v.21 no.1
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    • pp.100-106
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    • 2003
  • Purpose : To develop a patients' setup verification tool (PSVT) to verify the alignment of the machine and the target isocenters, and the reproduclbility of patients' setup for three dimensional conformal radiotherapy (3DCRT) and intensity modulated radiotherapy (IMRT). The utilization of this system is evaluated through phantom and patient case studies. Materials and methods : We developed and clinically tested a new method for patients' setup verification, using digitally reconstructed radiography (DRR), simulation, porial and digital images. The PSVT system was networked to a Pentium PC for the transmission of the acquired images to the PC for analysis. To verify the alignment of the machine and target isocenters, orthogonal pairs of simulation images were used as verification images. Errors in the isocenter alignment were measured by comparing the verification images with DRR of CT Images. Orthogonal films were taken of all the patients once a week. These verification films were compared with the DRR were used for the treatment setup. By performing this procedure every treatment, using humanoid phantom and patient cases, the errors of localization can be analyzed, with adjustments made from the translation. The reproducibility of the patients' setup was verified using portal and digital images. Results : The PSVT system was developed to verify the alignment of the machine and the target isocenters, and the reproducibility of the patients' setup for 3DCRT and IMRT. The results show that the localization errors are 0.8$\pm$0.2 mm (AP) and 1.0$\pm$0.3 mm (Lateral) in the cases relating to the brain and 1.1$\pm$0.5 mm (AP) and 1.0$\pm$0.6 mm (Lateral) in the cases relating to the pelvis. The reproducibility of the patients' setup was verified by visualization, using real-time image acquisition, leading to the practical utilization of our software Conclusions : A PSVT system was developed for the verification of the alignment between machine and the target isocenters, and the reproduclbility of the patients' setup in 3DCRT and IMRT. With adjustment of the completed GUI-based algorithm, and a good quality DRR image, our software may be used for clinical applications.

The pattern of movement and stress distribution during retraction of maxillary incisors using a 3-D finite element method (상악 전치부 후방 견인 시 이동 양상과 응력 분포에 관한 삼차원 유한요소법적 연구)

  • Chung, Ae-Jin;Kim, Un-Su;Lee, Soo-Haeng;Kang, Seong-Soo;Choi, Hee-In;Jo, Jin-Hyung;Kim, Sang-Cheol
    • The korean journal of orthodontics
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    • v.37 no.2 s.121
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    • pp.98-113
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    • 2007
  • Objective: The purpose of this study was to evaluate the displacement pattern and the stress distribution shown on a finite element model 3-D visualization of a dry human skull using CT during the retraction of upper anterior teeth. Methods: Experimental groups were differentiated into 8 groups according to corticotomy, anchorage (buccal: mini implant between the maxillary second premolar and first molar and second premolar reinforced with a mini Implant, palatal: mini implant between the maxillary first molar and second molar and mini implant on the midpalatal suture) and force application point (use of a power arm or not). Results: In cases where anterior teeth were retracted by a conventional T-loop arch wire, the anterior teeth tipped more postero-inferiorly and the posterior teeth moved slightly in a mesial direction. In cases where anterior teeth were retracted with corticotomy, the stress at the anterior bone segment was distributed widely and showed a smaller degree of tipping movement of the anterior teeth, but with a greater amount of displacement. In cases where anterior teeth were retracted from the buccal side with force applied to the mini implant placed between the maxillary second premolar and the first molar to the canine power arm, it showed that a smaller degree of tipping movement was generated than when force was applied to the second premolar reinforced with a mini implant from the canine bracket. In cases where anterior teeth were retracted from the palatal side with force applied to the mini implant on the midpalatal suture, it resulted in a greater degree of tipping movement than when force was applied to the mini implant between the maxillary first and second molars. Conclusion: The results of this study verifies the effects of corticotomies and the effects of controlling orthodontic force vectors during tooth movement.

Learning Material Bookmarking Service based on Collective Intelligence (집단지성 기반 학습자료 북마킹 서비스 시스템)

  • Jang, Jincheul;Jung, Sukhwan;Lee, Seulki;Jung, Chihoon;Yoon, Wan Chul;Yi, Mun Yong
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.179-192
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    • 2014
  • Keeping in line with the recent changes in the information technology environment, the online learning environment that supports multiple users' participation such as MOOC (Massive Open Online Courses) has become important. One of the largest professional associations in Information Technology, IEEE Computer Society, announced that "Supporting New Learning Styles" is a crucial trend in 2014. Popular MOOC services, CourseRa and edX, have continued to build active learning environment with a large number of lectures accessible anywhere using smart devices, and have been used by an increasing number of users. In addition, collaborative web services (e.g., blogs and Wikipedia) also support the creation of various user-uploaded learning materials, resulting in a vast amount of new lectures and learning materials being created every day in the online space. However, it is difficult for an online educational system to keep a learner' motivation as learning occurs remotely, with limited capability to share knowledge among the learners. Thus, it is essential to understand which materials are needed for each learner and how to motivate learners to actively participate in online learning system. To overcome these issues, leveraging the constructivism theory and collective intelligence, we have developed a social bookmarking system called WeStudy, which supports learning material sharing among the users and provides personalized learning material recommendations. Constructivism theory argues that knowledge is being constructed while learners interact with the world. Collective intelligence can be separated into two types: (1) collaborative collective intelligence, which can be built on the basis of direct collaboration among the participants (e.g., Wikipedia), and (2) integrative collective intelligence, which produces new forms of knowledge by combining independent and distributed information through highly advanced technologies and algorithms (e.g., Google PageRank, Recommender systems). Recommender system, one of the examples of integrative collective intelligence, is to utilize online activities of the users and recommend what users may be interested in. Our system included both collaborative collective intelligence functions and integrative collective intelligence functions. We analyzed well-known Web services based on collective intelligence such as Wikipedia, Slideshare, and Videolectures to identify main design factors that support collective intelligence. Based on this analysis, in addition to sharing online resources through social bookmarking, we selected three essential functions for our system: 1) multimodal visualization of learning materials through two forms (e.g., list and graph), 2) personalized recommendation of learning materials, and 3) explicit designation of learners of their interest. After developing web-based WeStudy system, we conducted usability testing through the heuristic evaluation method that included seven heuristic indices: features and functionality, cognitive page, navigation, search and filtering, control and feedback, forms, context and text. We recruited 10 experts who majored in Human Computer Interaction and worked in the same field, and requested both quantitative and qualitative evaluation of the system. The evaluation results show that, relative to the other functions evaluated, the list/graph page produced higher scores on all indices except for contexts & text. In case of contexts & text, learning material page produced the best score, compared with the other functions. In general, the explicit designation of learners of their interests, one of the distinctive functions, received lower scores on all usability indices because of its unfamiliar functionality to the users. In summary, the evaluation results show that our system has achieved high usability with good performance with some minor issues, which need to be fully addressed before the public release of the system to large-scale users. The study findings provide practical guidelines for the design and development of various systems that utilize collective intelligence.