• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.74-83
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• 2018

This study analyzed the differences in effectiveness between celebrity and consumer endorsers by type of story in storytelling ads. A $2{\times}2$ factorial design experiment was conducted: the type of advertising endorser (celebrity, consumer) and the type of story (life experience, brand myth). 200 women in their 30s and 40s participated in an online survey. Study shows that for a life-experience ad, the consumer model has higher advertising effectiveness than the celebrity endorser for all three dependent variables : ad attitude, brand attitude, and purchase intent. In the case of brand-myth ad, the celebrity endorser had more favorable ad attitude than the consumer endorser did, while there was no difference in brand attitude and purchase intent. The theoretical and practical implications of the study were discussed in the conclusion.

• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.89-104
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• 2007

This research attempts to give a personalized recommendation framework in large-sized music contents environment. Despite of existing studios and commercial contents for recommendation systems, large online shopping malls are still looking for a recommendation system that can serve personalized recommendation and handle large data in real-time. This research utilizes data mining technologies and new pattern matching algorithm. A clustering technique is used to get dynamic user segmentations using user preference to contents categories. Then a sequential pattern mining technique is used to extract contents access patterns in the user segmentations. And the recommendation is given by our recommendation algorithm using user contents preference history and contents access patterns of the segment. In the framework, preprocessing and data transformation and transition are implemented on DBMS. The proposed system is implemented to show that the framework is feasible. In the experiment using real-world large data, personalized recommendation is given in almost real-time and shows acceptable correctness.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.39-49
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• 2017

As the Internet technology advances, data on the web is increasing sharply. Many research study about incremental learning for classifying effectively in data increasing. Web document contains the time-series data such as published date. If we reflect time-series data to classification, it will be an effective classification. In this study, we analyze the time-series variation of the words. We propose an efficient classification through dividing the dataset based on the analysis of time-series information. For experiment, we corrected 1 million online news articles including time-series information. We divide the dataset and classify the dataset using SVM and $Na{\ddot{i}}ve$ Bayes. In each model, we show that classification performance is increasing. Through this study, we showed that reflecting time-series information can improve the classification performance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1103-1110
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• 2013

This paper proposes a method of identifying ownership of personal information in Social Network Service. In detail, the proposed method automatically decides whether any location information mentioned in twitter indicates the publisher's residence area. Identifying ownership of personal information is necessary part of evaluating risk of opened personal information online. The proposed method uses a set of decision rules that considers 13 features that are lexicographic and syntactic characteristics of the tweet sentences. In an experiment using real twitter data, the proposed method shows better performance (f1-score: 0.876) than the conventional document classification models such as naive bayesian that uses n-gram as a feature set.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.296-307
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• 2020

Permanent magnet sodium flowmeter (PMSF) have been used to measure the sodium flow in fast breeder reactors. Due to the effects of irradiation, thermal cycling, time lapse, etc., the magnetic flux density of the PMSF will decrease after being used in the reactor for a period of time. Therefore, it must be calibrated regularly. But some flowmeters that immersed in sodium cannot be removed for an off-line calibration, so the on-line calibration is required. However, the best online calibration accuracy of PMSF using cross-correlation analysis method was 2.0-level without considering the repeatability. In order to further improve this work, the operational principle of the transducer in PMSF is analyzed and the design principle of the transducer is proposed. The transducers were tested on the sodium flow loop to collect the experimental data. The signal characteristics are analyzed from the time and frequency domains, respectively. The cross-correlation analysis method based on biased estimation is adopted to obtain the flow rate. The verification experimental results showed that the measurement accuracy is 1.0-level when the flow velocity is above 0.5 m/s, and the measurement accuracy is 3.0-level when the flow velocity is in the range of 0.2 m/s to 0.5 m/s.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.125-134
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• 2014

As the social media which was simple communication media is activated on account of twitter and facebook, it's usability and importance are growing recently. Although many companies are making full use of its the capacity of information diffusion for marketing, the adverse effects of this capacity are growing. Because social network is formed and communicates based on friendships and relationships, the spreading speed of the spam and mal-ware is very swift. In this paper, we draw parameters affecting malicious data diffusion in social network environment, and compare and analyze the diffusion capacity of each parameters by propagation experiment with XSS Worm and Koobface Worm. In addition, we discuss the structural characteristics of social network environment and then proposed malicious data propagation model based on parameters affecting information diffusion. n this paper, we made up BA and HK models based on SI model, dynamic model, to conduct the experiments, and as a result of the experiments it was proved that parameters which effect on propagation of XSS Worm and Koobface Worm are clustering coefficient and closeness centrality.

• Journal of KIISE:Software and Applications
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• v.37 no.12
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• pp.946-950
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• 2010

Many sentiment categorization systems based on machine learning methods use morphological analyzers in order to extract linguistic features from sentences. However, the morphological analyzers do not generally perform well in a customer review domain because online customer reviews include many spacing errors and spelling errors. These low performances of the underlying systems lead to performance decreases of the sentiment categorization systems. To resolve this problem, we propose a feature extraction method based on simple longest matching of Eojeol (a Korean spacing unit) and phoneme patterns. The two kinds of patterns are automatically constructed from a large amount of POS (part-of-speech) tagged corpus. Eojeol patterns consist of Eojeols including content words such as nouns and verbs. Phoneme patterns consist of leading consonant and vowel pairs of predicate words such as verbs and adjectives because spelling errors seldom occur in leading consonants and vowels. To evaluate the proposed method, we implemented a sentiment categorization system using a SVM (Support Vector Machine) as a machine learner. In the experiment with Korean customer reviews, the sentiment categorization system using the proposed method outperformed that using a morphological analyzer as a feature extractor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.170-171
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• 2013

In aspect of HCI(Human Computer Interaction) gameplay is the procedure to solve the problem that gamers encounter in order to generate or discover a new rule to achieve gamers' goal. The goal of this research is to investigate the structure and understand the gameplay in aspect of affordance from ecological psychology rather than the traditional problem solving theory. This research selects 'World of Warcraft' as MMORPG(Massively Multiplayer Online Role Playing Game). Five expert gamers participated in this experiment. We record all gameplay using audio and video device. We conducted protocol analysis as qualitative method based on the verbal report and action protocol during game playing. As result, gameplay based on affordance includes selection and relation. We found that subjects selected one thing at once with attention. Moreover, we found that there were two behaviors : exploratory action and performatory action. We believe that learning, utilization, and transformation for affordance appear. The result of this research imply to suggest design guideline for game design methodology when designers develop game.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.306-314
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• 2004

Some receiver(and most transmit) beamforming algorithms with an array antenna at a cellular CDMA base stations require accurate internal and external calibrations. The external calibration, which usually needs to be done only once, determines the array manifolds, i.e. the complex response of each antenna as a function of DOA(Directions of Arrival). The internal calibrations are necessary because characteristics of RF/IF circuity of each receiver chain vary differently in response to temperature or humidity changes. We propose an iterative subspace-based calibration algorithm for an asynchronous CDMA-based antenna away in the presence of unknown gain and phase error is presented. We verify the subspace-based calibration algorithms by performing the experiment using measured data. Also, we propose an efficient algorithm using the simulated annealing technique. This algorithm overcomes the problem of the initial guessing in the subspace-based approach.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.91-97
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• 2016

The technological environment is rapidly affecting the way of shopping. When consumers go about retail activities, they not only use a single channel (e.g., traditional stores, mobile) but also combine different channels. This research focuses on the factors which influence the favorableness toward omni-channel shopping. Specifically, this paper investigates the effect of extraversion-introversion on the omni-channel shopping favorableness. Moreover, the effect of variety-seeking tendency is examined as a mediator. The results of an experiment using PROCESS program find that when participants are more extravert, they show greater favorableness toward omni-channel shopping and variety-seeking tendency mediates the effect of extraversion-introversion. Based on the findings, this research proposes managerial implications and several directions for further research.