• Journal of information and communication convergence engineering
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• 제17권4호
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• pp.239-245
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• 2019

Recently, effort to obtain various information from the vast amount of social network services (SNS) big data generated in daily life has expanded. SNS big data comprise sentences classified as unstructured data, which complicates data processing. As the amount of processing increases, a rapid processing technique is required to extract valuable information from SNS big data. We herein propose a system that can extract human sentiment information from vast amounts of SNS unstructured big data using the naïve Bayes algorithm and natural language processing (NLP). Furthermore, we analyze the effectiveness of the proposed method through various experiments. Based on sentiment accuracy analysis, experimental results showed that the machine learning method using the naïve Bayes algorithm afforded a 63.5% accuracy, which was lower than that yielded by the NLP method. However, based on data processing speed analysis, the machine learning method by the naïve Bayes algorithm demonstrated a processing performance that was approximately 5.4 times higher than that by the NLP method.

• Journal of Information Processing Systems
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• 제15권3호
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• pp.500-519
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• 2019

The blooming of social media has simulated interest in sentiment analysis. Sentiment analysis aims to determine from a specific piece of content the overall attitude of its author in relation to a specific item, product, brand, or service. In sentiment analysis, the focus is on the subjective sentences. Hence, in order to discover and extract the subjective information from a given text, researchers have applied various methods in computational linguistics, natural language processing, and text analysis. The aim of this paper is to provide an in-depth up-to-date study of the sentiment analysis algorithms in order to familiarize with other works done in the subject. The paper focuses on the main tasks and applications of sentiment analysis. State-of-the-art algorithms, methodologies and techniques have been categorized and summarized to facilitate future research in this field.

• 수산해양교육연구
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• 제24권3호
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• pp.424-435
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• 2012

This study aimed to examine the influences of children's sex and the social information interpretation(intentional/incidental) on aggressions (form/function). The subjects were 363 fifth and sixth graders from 6 elementary schools in Busan and the data were analyzed with two-way ANOVA. The research findings were as follows: First, children's sex had significant influence upon their overt aggression, and children's interpretation of social information had significant influences upon their overt aggression and relational aggression alike. Second, children's sex and interpretation of social information had significant influences upon their proactive aggression and reactive aggression. Finally, children's sex had significant influences upon proactive-overt aggression, reactive-overt aggression and proactive-relational aggression.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권5호
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• pp.2211-2232
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• 2018

The unstructured and semi-structured big data in social network poses new challenges in query retrieval. This requirement needs to be met by introducing quality retrieval time measures like indexing. Due to the huge volume of data storage, there originate the need for efficient index algorithms to promote query processing. However, conventional algorithms fail to index the huge amount of frequently obtained information in real time and fall short of providing scalable indexing service. In this paper, a new LIndex algorithm, which is a heuristic on Lucene is built on Neo4jHA architecture that holds the social network Big data. LIndex is a flexible and simplified adaptive indexing scheme that ascendancy decomposed shortest paths around term neighbors as basic indexing unit. This newfangled index proves to be effectual in query space pruning of graph database Neo4j, scalable in index construction and deployment. A graph query is processed and optimized beyond the traditional Lucene in a time-based manner to a more efficient path method in LIndex. This advanced algorithm significantly reduces query fetch without compromising the quality of results in time. The experiments are conducted to confirm the efficiency of the proposed query retrieval in Neo4j graph NoSQL database.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2011년도 춘계학술발표대회
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• pp.544-546
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• 2011

Due to the explosive growth of online social network users, large numbers of users discover these social network sites are a place where they can be able to spend their spare time, share feelings, ideas freely, and to search for new friends or partners. These web sites give an opportunity for its users to socialize with new people and to keep in touch or reconnect with current or old friends and families across disperse continents via these web sites, which traditionally replace the traditional methods. These social network web sites need careful investigations and findings on the usability for effective interactivity and more usability. However, little research might have previously invested on the usability of these on social network web sites. Therefore, we propose a new framework to study the usability of these social network sites. We namely call our framework "Interactivity". This framework will enable us to assess the usability of the social network sites. It will provide an overview of the user's behavior while interacting in these social network web sites. Measurement of the interactivity will be measured using Camtasia software. This software will entirely capture the interactivity of users including the screen and the movements, which the screen and the motion of the user action will undergo to analysis at the end of our research.

• 아동학회지
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• 제31권6호
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• pp.15-34
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• 2010

The present study examines the sex differences in 5-year-old preschoolers' aggression according to the type of aggression (overt, relational) and the effect of components of social information processing (SIP : interpretation, goal clarification, response generation, response evaluation) and emotional factors (emotionality, emotional knowledge, emotion regulation) on their aggression. The subjects were 112 5-year-olds (56 boys, 56 girls) and their 11 teachers recruited from 9 day-care centers in Seoul and Kyung-Ki province. Each child's SIP and emotional knowledge were individually assessed with pictorial tasks and teachers reported on children's aggression, emotionality, and emotion regulation by questionnaires. Results indicated that there was a significant sex difference only in the preschoolers' overt aggression. Overtly aggressive response generation in SIP was the strongest predictor of preschoolers' overt aggression while anger of negative emotionality in emotional factors was the strongest predictor of preschoolers' relational aggression.

• Journal of Information Processing Systems
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• 제17권2호
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• pp.213-226
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• 2021

Given that most of the link prediction algorithms for signed social networks can only complete sign prediction, a novel algorithm is proposed aiming to achieve both link prediction and sign prediction in signed networks. Based on the structural balance theory, the local link tightness and global link tightness are defined respectively by using the structural information of paths with the step size of 2 and 3 between the two nodes. Then the total similarity of the node pair can be obtained by combining them. Its absolute value measures the possibility of the two nodes to establish a link, and its sign is the sign prediction result of the predicted link. The effectiveness and correctness of the proposed algorithm are verified on six typical datasets. Comparison and analysis are also carried out with the classical prediction algorithms in signed networks such as CN-Predict, ICN-Predict, and PSNBS (prediction in signed networks based on balance and similarity) using the evaluation indexes like area under the curve (AUC), Precision, improved AUC', improved Accuracy', and so on. Results show that the proposed algorithm achieves good performance in both link prediction and sign prediction, and its accuracy is higher than other algorithms. Moreover, it can achieve a good balance between prediction accuracy and computational complexity.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2013년도 춘계학술발표대회
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• pp.117-120
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• 2013

스마트폰의 보급으로 모바일 소셜 네트워크 게임(SNG: Social Network Game)을 즐기는 사용자들이 증가하고 있다. 그러나, SNG의 특성에 맞는 자원 활용률을 고려한 효율적인 게임서버에 대한 연구는 매우 부족한 실정이다. 본 논문은 가상화 기반으로 SNG게임서버를 설계 및 구현한다. 또한 가상화 기반 분산 게임서버의 CPU 사용률과 Memory 사용량을 분석하여 게임서버의 자원 활용률을 보인다. 이를 토대로 SNG게임서버 환경구축의 기반지식을 제공한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권11호
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• pp.2827-2848
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• 2012

Previously, we described a social media cloud computing service environment (SMCCSE). This SMCCSE supports the development of social networking services (SNSs) that include audio, image, and video formats. A social media cloud computing PaaS platform, a core component in a SMCCSE, processes large amounts of social media in a parallel and distributed manner for supporting a reliable SNS. Here, we propose a Hadoop-based multimedia system for image and video transcoding processing, necessary functions of our PaaS platform. Our system consists of two modules, including an image transcoding module and a video transcoding module. We also design and implement the system by using a MapReduce framework running on a Hadoop Distributed File System (HDFS) and the media processing libraries Xuggler and JAI. In this way, our system exponentially reduces the encoding time for transcoding large amounts of image and video files into specific formats depending on user-requested options (such as resolution, bit rate, and frame rate). In order to evaluate system performance, we measure the total image and video transcoding time for image and video data sets, respectively, under various experimental conditions. In addition, we compare the video transcoding performance of our cloud-based approach with that of the traditional frame-level parallel processing-based approach. Based on experiments performed on a 28-node cluster, the proposed Hadoop-based multimedia transcoding system delivers excellent speed and quality.

• 한국문헌정보학회지
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• 제24권
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• pp.221-261
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• 1993

The production, storage, processing and distribution of information is fast becoming a major economic activity for many nations of the world. The basic idea of this study is that knowledge and information are becoming the strategic resources and transforming agents in the information society. Therefore, in order to cope with successfully the transition toward the information society, the development of measurement tools and social indicators is essential. The purpose of this study is to fulfill three major objectives with regard to the analysis of the information sector in the information society. (1) This study suggests the theoretical definitions and social indicators of the information society. (2) This study investigates an empirical study of the information sector consisting of information industry, information workforce, and information indicator of the selected nations. (3) It advances theoretical explanations of the major factors of the growth of the information sector, and develops theoretical hypothesis and explanations of the information society.