• Title/Summary/Keyword: Text features

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Production Date and Patrons of Korean Treasure #978: Transcription of the Avatamsaka Sutra (Zhou Version) in Gold on White Paper (보물 제978호 <백지금니대방광불화엄경(白紙金泥大方廣佛華嚴經) 권(卷)29>의 조성 연대 및 발원자 고찰)

  • Won, Seunghyun
    • MISULJARYO - National Museum of Korea Art Journal
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    • v.98
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    • pp.78-103
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    • 2020
  • Transcribed Buddhist sutras generally consist of a frontispiece illustration, sutra illustrations, and sutra text, although some parts may be lost over time. Most transcribed sutras originally include an official record of the transcription (saseonggi) at either the beginning or end of the volume, which document various details of the production, including who commissioned the sutra and when it was transcribed. If such records are unavailable or difficult to decipher, the date of the sutra can only be estimated by comparison to other works with known production dates. This is the case with Korean Treasure #978, the "Transcription of the Avatamsaka Sutra (Zhou Version) in Gold on White Paper" (hereinafter, "Avatamsaka Sutra, Volume 29"), which does not contain any details of its production. Based on formal comparisons, the volume has been estimated to date from the early Joseon period. Important criteria for estimating the production date include the type of calligraphy script and the overall expression of the sutra illustrations. However, these features are missing from some early Joseon sutras, making it difficult to definitively assert which characteristics are representative of the period. Also, transcribed sutras from the late Goryeo period (after 1350) and early Joseon period are often very similar in terms of the expression of the frontispiece illustrations and sutra illustrations. From the late Goryeo period through the early Joseon period, the illustrations of transcribed sutras, which had previously been relatively detailed and realistic, gradually became more formalized and stylized. Significantly, Avatamsaka Sutra, Volume 29 includes illustrations showing both styles of expression (i.e., realistic and formalized). Moreover, the hemp leaf design on the frontispiece and the border around the sutra illustrations are unique features that have never been seen on any other transcribed sutras. Notably, however, Avatamsaka Sutra in Gold on White Paper, Volume 26 (hereinafter, "Avatamsaka Sutra, Volume 26"), which has not yet been introduced in academic research, is complete with frontispiece, sutra illustrations, and sutra text. This sutra is identical to Avatamsaka Sutra, Volume 29 in size, composition, and details, and is thus estimated to have been produced at the same time and by the same patrons. According to the record at the end of the volume, Avatamsaka Sutra, Volume 26 was commissioned in 1348 by Gi Cheol (d. 1365), which corresponds to the estimated date of Avatamsaka Sutra, Volume 29 derived by formal comparison. Based on this new information, Avatamsaka Sutra, Volume 29 was likely produced in the late Goryeo period rather than the early Joseon period, as has previously been presumed. The new study of Avatamsaka Sutra, Volume 26 also seems to confirm that both sutras were transcribed by highly skilled artisans in 1348 of the late Goryeo period, a transitional phase in the expression of sutra illustrations.

A Study on the Wooden Seated Vairocana Tri-kaya Buddha Images in the Daeungjeon Hall of Hwaeomsa Temple (화엄사 대웅전 목조비로자나삼신 불좌상에 대한 고찰)

  • Choe, Songeun
    • MISULJARYO - National Museum of Korea Art Journal
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    • v.100
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    • pp.140-170
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    • 2021
  • This paper investigates the Wooden Seated Tri-kaya Buddha Images(三身佛像) of Vairocana, Rushana, and Sakyamuni enshrined in Daeungjeon Hall of Hwaeomsa temple(華嚴寺) in Gurae, South Cheolla Province. They were produced in 1634 CE and placed in 1635 CE, about forty years after original images made in the Goryeo period were destroyed by the Japanese army during the war. The reconstruction of Hwaeomsa was conducted by Gakseong, one of the leading monks of Joseon Dynasty in the 17th century, who also conducted the reconstructions of many Buddhist temples after the war. In 2015, a prayer text (dated 1635) concerning the production of Hwaeomsa Tri-kaya Buddha images was found in the repository within Sakyamuni Buddha. It lists the names of participants, including royal family members (i.e., prince Yi Guang, the eighth son of King Seon-jo), and their relatives (i.e., Sin Ik-seong, son-in-law of King Seonjo), court ladies, monk-sculptors, and large numbers of monks and laymen Buddhists. A prayer text (dated 1634) listing the names of monk-sculptors written on the wooden panel inside the pedestal of Rushana Buddha was also found. A recent investigation into the repository within Rushana Buddha in 2020 CE has revealed a prayer text listing participants producing these images, similar to the former one from Sakyamuni Buddha, together with sacred relics of hoo-ryeong-tong copper bottle and a large quantity of Sutra books. These new materials opened a way to understand Hwaeomsa Trikaya images, including who made them and when they were made. The two above-mentioned prayer texts from the repository of Sakyamuni and Rushana Buddha statues, and the wooden panel inside the pedestal of Rushan Buddha tell us that eighteen monk-sculptors, including Eungwon, Cheongheon and Ingyun, who were well-known monk artisans of the 17th century, took part in the construction of these images. As a matter of fact, Cheongheon belonged to a different workshop from Eungwon and Ingyun, who were most likely teacher and disciple or senior and junior colleagues, which means that the production of Hwaeomsa Tri-kaya Buddha images was a collaboration between sculptors from two workshops. Eungwon and Ingyun seem to have belonged to the same community studying under the great Buddhist priest Seonsu, the teacher of Monk Gakseong who was in charge of the reconstruction of Haweonsa temple. Hwaeomsa Tri-kaya Buddha images show a big head, a squarish face with plump cheeks, narrow and drooping shoulders, and a short waist, which depict significant differences in body proportion to those of other Buddha statues of the first half of 17th century, which typically have wide shoulders and long waists. The body proportion shown in the Hwaeomsa images could be linked with images of late Goryeo and early Joseon period. Rushana Buddha, raising his two arms in a preaching hand gesture and wearing a crown and bracelets, shows unique iconography of the Bodhisattva form. This iconography of Rushana Buddha had appeared in a few Sutra paintings of Northern Song and Late Goryeo period of 13th and 14th century. BodhaSri-mudra of Vairocana Buddha, unlike the general type of BodhaSri-mudra that shows the right hand holding the left index finger, places his right hand upon the left hand in a fist. It is similar to that of Vairocana images of Northern and Southern Song, whose left hand is placed on the top of right hand in a fist. This type of mudra was most likely introduced during the Goryeo period. The dried lacquer Seated Vairocana image of Bulheosa Temple in Naju is datable to late Goryeo period, and exhibits similar forms of the mudra. Hwaeomsa Tri-kaya Buddha images also show new iconographic aspects, as well as traditional stylistic and iconographic features. The earth-touching (bhumisparsa) mudra of Sakymuni Buddha, putting his left thumb close to the middle finger, as if to make a preaching mudra, can be regarded as a new aspect that was influenced by the Sutra illustrations of the Ming dynasty, which were imported by the royal court of Joseon dynasty and most likely had an impact on Joseon Buddhist art from the 15th and 16th centuries. Stylistic and iconographical features of Hwaeomsa Tri-kaya Buddha images indicate that the traditional aspects of Goryeo period and new iconography of Joseon period are rendered together, side by side, in these sculptures. The coexistence of old and new aspects in one set of images could indicate that monk sculptors tried to find a new way to produce Hwaeomsa images based on the old traditional style of Goryeo period when the original Tri-kaya Buddha images were made, although some new iconography popular in Joseon period was also employed in the images. It is also probable that monk sculptors of Hwaeomsa Tri-kaya Buddha images intended to reconstruct these images following the original images of Goryeo period, which was recollected by surviving monks at Hwaeomsa, who had witnessed the original Tri-kaya Buddha images.

A Study on Analysis of consumer perception of YouTube advertising using text mining (텍스트 마이닝을 활용한 Youtube 광고에 대한 소비자 인식 분석)

  • Eum, Seong-Won
    • Management & Information Systems Review
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    • v.39 no.2
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    • pp.181-193
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    • 2020
  • This study is a study that analyzes consumer perception by utilizing text mining, which is a recent issue. we analyzed the consumer's perception of Samsung Galaxy by analyzing consumer reviews of Samsung Galaxy YouTube ads. for analysis, 1,819 consumer reviews of YouTube ads were extracted. through this data pre-processing, keywords for advertisements were classified and extracted into nouns, adjectives, and adverbs. after that, frequency analysis and emotional analysis were performed. Finally, clustering was performed through CONCOR. the summary of this study is as follows. the first most frequently mentioned words were Galaxy Note (n = 217), Good (n = 135), Pen (n = 40), and Function (n = 29). it can be judged through the advertisement that consumers "Galaxy Note", "Good", "Pen", and "Features" have good functional aspects for Samsung mobile phone products and positively recognize the Note Pen. in addition, the recognition of "Samsung Pay", "Innovation", "Design", and "iPhone" shows that Samsung's mobile phone is highly regarded for its innovative design and functional aspects of Samsung Pay. second, it is the result of sentiment analysis on YouTube advertising. As a result of emotional analysis, the ratio of emotional intensity was positive (75.95%) and higher than negative (24.05%). this means that consumers are positively aware of Samsung Galaxy mobile phones. As a result of the emotional keyword analysis, positive keywords were "good", "good", "innovative", "highest", "fast", "pretty", etc., negative keywords were "frightening", "I want to cry", "discomfort", "sorry", "no", etc. were extracted. the implication of this study is that most of the studies by quantitative analysis methods were considered when looking at the consumer perception study of existing advertisements. In this study, we deviated from quantitative research methods for advertising and attempted to analyze consumer perception through qualitative research. this is expected to have a great influence on future research, and I am sure that it will be a starting point for consumer awareness research through qualitative research.

User Centered Interface Design of Web-based Attention Testing Tools: Inhibition of Return(IOR) and Graphic UI (웹 기반 주의력 검사의 사용자 인터페이스 설계: 회귀억제 과제와 그래픽 UI를 중심으로)

  • Kwahk, Ji-Eun;Kwak, Ho-Wan
    • Korean Journal of Cognitive Science
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    • v.19 no.4
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    • pp.331-367
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    • 2008
  • This study aims to validate a web-based neuropsychological testing tool developed by Kwak(2007) and to suggest solutions to potential problems that can deteriorate its validity. When it targets a wider range of subjects, a web-based neuropsychological testing tool is challenged by high drop-out rates, lack of motivation, lack of interactivity with the experimenter, fear of computer, etc. As a possible solution to these threats, this study aims to redesign the user interface of a web-based attention testing tool through three phases of study. In Study 1, an extensive analysis of Kwak's(2007) attention testing tool was conducted to identify potential usability problems. The Heuristic Walkthrough(HW) method was used by three usability experts to review various design features. As a result, many problems were found throughout the tool. The findings concluded that the design of instructions, user information survey forms, task screen, results screen, etc. did not conform to the needs of users and their tasks. In Study 2, 11 guidelines for the design of web-based attention testing tools were established based on the findings from Study 1. The guidelines were used to optimize the design and organization of the tool so that it fits to the user and task needs. The resulting new design alternative was then implemented as a working prototype using the JAVA programming language. In Study 3, a comparative study was conducted to demonstrate the excellence of the new design of attention testing tool(named graphic style tool) over the existing design(named text style tool). A total of 60 subjects participated in user testing sessions where their error frequency, error patterns, and subjective satisfaction were measured through performance observation and questionnaires. Through the task performance measurement, a number of user errors in various types were observed in the existing text style tool. The questionnaire results were also in support of the new graphic style tool, users rated the new graphic style tool higher than the existing text style tool in terms of overall satisfaction, screen design, terms and system information, ease of learning, and system performance.

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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.

Research on hybrid music recommendation system using metadata of music tracks and playlists (음악과 플레이리스트의 메타데이터를 활용한 하이브리드 음악 추천 시스템에 관한 연구)

  • Hyun Tae Lee;Gyoo Gun Lim
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.145-165
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    • 2023
  • Recommendation system plays a significant role on relieving difficulties of selecting information among rapidly increasing amount of information caused by the development of the Internet and on efficiently displaying information that fits individual personal interest. In particular, without the help of recommendation system, E-commerce and OTT companies cannot overcome the long-tail phenomenon, a phenomenon in which only popular products are consumed, as the number of products and contents are rapidly increasing. Therefore, the research on recommendation systems is being actively conducted to overcome the phenomenon and to provide information or contents that are aligned with users' individual interests, in order to induce customers to consume various products or contents. Usually, collaborative filtering which utilizes users' historical behavioral data shows better performance than contents-based filtering which utilizes users' preferred contents. However, collaborative filtering can suffer from cold-start problem which occurs when there is lack of users' historical behavioral data. In this paper, hybrid music recommendation system, which can solve cold-start problem, is proposed based on the playlist data of Melon music streaming service that is given by Kakao Arena for music playlist continuation competition. The goal of this research is to use music tracks, that are included in the playlists, and metadata of music tracks and playlists in order to predict other music tracks when the half or whole of the tracks are masked. Therefore, two different recommendation procedures were conducted depending on the two different situations. When music tracks are included in the playlist, LightFM is used in order to utilize the music track list of the playlists and metadata of each music tracks. Then, the result of Item2Vec model, which uses vector embeddings of music tracks, tags and titles for recommendation, is combined with the result of LightFM model to create final recommendation list. When there are no music tracks available in the playlists but only playlists' tags and titles are available, recommendation was made by finding similar playlists based on playlists vectors which was made by the aggregation of FastText pre-trained embedding vectors of tags and titles of each playlists. As a result, not only cold-start problem can be resolved, but also achieved better performance than ALS, BPR and Item2Vec by using the metadata of both music tracks and playlists. In addition, it was found that the LightFM model, which uses only artist information as an item feature, shows the best performance compared to other LightFM models which use other item features of music tracks.

Export Control System based on Case Based Reasoning: Design and Evaluation (사례 기반 지능형 수출통제 시스템 : 설계와 평가)

  • Hong, Woneui;Kim, Uihyun;Cho, Sinhee;Kim, Sansung;Yi, Mun Yong;Shin, Donghoon
    • Journal of Intelligence and Information Systems
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    • v.20 no.3
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    • pp.109-131
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    • 2014
  • As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

Designing a Writing Support System Based on Narrative Comprehension of Readers (독자의 내러티브 이해를 반영한 창작 지원 시스템 설계)

  • Kwon, Hochang;Kwon, Hyuk Tae;Yoon, Wan Chul
    • Journal of the HCI Society of Korea
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    • v.9 no.2
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    • pp.23-31
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    • 2014
  • A variety of writing support systems focus on the information management or the feature analysis of the commercially successful narrative texts. In these approaches, the reader's role in the narrative creating process is overlooked. During a writing work, an author anticipates the reader's response or expectation to the narrative and he/she organizes the narrative either along or against the prediction about readers. Assessing and controlling the reader's comprehension in the development of events influences the aesthetic quality of the narrative. In this paper, we suggest a writing support system to visualize and adjust the characteristics of a narrative text related to the reader's comprehension, which is theoretically based on the narrative structure model and the event-indexing situation model. Under the development of the support system, we designed an interactive framework to create events as the basic units of story and arrange them onto both story- and discourse-time axes. Using this framework, we analyzed the organization of events about an actual film narrative. We also proposed both the continuity of the situational dimensions and the cognitive complexity as the characteristics to affect the reader's comprehension, hence we devised a method to visualize and evaluate them. This method was applied to the actual film narrative and the result was discussed in the aspect of the features of the narrative and wiring support strategies.

A Method for Measuring and Evaluating for Block-based Programming Code (블록기반 프로그래밍 코드의 수준 및 취약수준 측정방안)

  • Sohn, Wonsung
    • Journal of The Korean Association of Information Education
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    • v.20 no.3
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    • pp.293-302
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    • 2016
  • It is the latest fashion of interesting with software education in public school environment and also consider as high priority issue of curriculum for college freshman with programming 101 courses. The block-based programming tool is used widely for the beginner and provides several positive features compare than text-based programming language tools. To measure quality of programming code elaborately which is based script language, it is need to very tough manual process. As a result the previously research related with evaluation of block-based script code has been focused very simple methods in which normalize the number of blocks used which is related with programming concept. In such cases in this, it is difficult to measure structural vulnerability of script code and implicit programming concept which does not expose. In this research, the framework is proposed which enable to measure and evaluate quality of code script of block-based programming tools and also provides method to find of vulnerability of script code. In this framework, the quality metrics is constructed to structuralize implicit programming concept and then developed the quality measure and vulnerability model of script to improve level of programming. Consequently, the proposed methods enable to check of level of programming and predict the heuristic target level.

Accelerated Loarning of Latent Topic Models by Incremental EM Algorithm (점진적 EM 알고리즘에 의한 잠재토픽모델의 학습 속도 향상)

  • Chang, Jeong-Ho;Lee, Jong-Woo;Eom, Jae-Hong
    • Journal of KIISE:Software and Applications
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    • v.34 no.12
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    • pp.1045-1055
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    • 2007
  • Latent topic models are statistical models which automatically captures salient patterns or correlation among features underlying a data collection in a probabilistic way. They are gaining an increased popularity as an effective tool in the application of automatic semantic feature extraction from text corpus, multimedia data analysis including image data, and bioinformatics. Among the important issues for the effectiveness in the application of latent topic models to the massive data set is the efficient learning of the model. The paper proposes an accelerated learning technique for PLSA model, one of the popular latent topic models, by an incremental EM algorithm instead of conventional EM algorithm. The incremental EM algorithm can be characterized by the employment of a series of partial E-steps that are performed on the corresponding subsets of the entire data collection, unlike in the conventional EM algorithm where one batch E-step is done for the whole data set. By the replacement of a single batch E-M step with a series of partial E-steps and M-steps, the inference result for the previous data subset can be directly reflected to the next inference process, which can enhance the learning speed for the entire data set. The algorithm is advantageous also in that it is guaranteed to converge to a local maximum solution and can be easily implemented just with slight modification of the existing algorithm based on the conventional EM. We present the basic application of the incremental EM algorithm to the learning of PLSA and empirically evaluate the acceleration performance with several possible data partitioning methods for the practical application. The experimental results on a real-world news data set show that the proposed approach can accomplish a meaningful enhancement of the convergence rate in the learning of latent topic model. Additionally, we present an interesting result which supports a possible synergistic effect of the combination of incremental EM algorithm with parallel computing.