• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.8
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• pp.195-202
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• 2018

With the development of location-based applications such as smart phones and GPS navigation, active research is being conducted to protect location and trajectory privacy. To receive location-related services, users must disclose their exact location to the server. However, disclosure of users' location exposes not only their locations but also their trajectory to the server, which can lead to concerns of privacy violation. Furthermore, users request from the server not only location information but also multimedia information (photographs, reviews, etc. of the location), and this increases the processing cost of the server and the information to be received by the user. To solve these problems, this study proposes the EGTC (Enhanced Grid-based Trajectory Cloaking) technique. As with the existing GTC (Grid-based Trajectory Cloaking) technique, EGTC method divides the user trajectory into grids at the user privacy level (UPL) and creates a cloaking region in which a random query sequence is determined. In the next step, the necessary information is received as index by considering the sub-grid cell corresponding to the path through which the user wishes to move as c(x,y). The proposed method ensures the trajectory privacy as with the existing GTC method while reducing the amount of information the user must listen to. The excellence of the proposed method has been proven through experimental results.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.71-89
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• 2016

Sentiment analysis is used for identifying emotions or sentiments embedded in the user generated data such as customer reviews from blogs, social network services, and so on. Various research fields such as computer science and business management can take advantage of this feature to analyze customer-generated opinions. In previous studies, the star rating of a review is regarded as the same as sentiment embedded in the text. However, it does not always correspond to the sentiment polarity. Due to this supposition, previous studies have some limitations in their accuracy. To solve this issue, the present study uses a supervised sentiment classification model to measure a more accurate sentiment polarity. This study aims to propose an advanced sentiment classifier and to discover the correlation between movie reviews and box-office success. The advanced sentiment classifier is based on two supervised machine learning techniques, the Support Vector Machines (SVM) and Feedforward Neural Network (FNN). The sentiment scores of the movie reviews are measured by the sentiment classifier and are analyzed by statistical correlations between movie reviews and box-office success. Movie reviews are collected along with a star-rate. The dataset used in this study consists of 1,258,538 reviews from 175 films gathered from Naver Movie website (movie.naver.com). The results show that the proposed sentiment classifier outperforms Naive Bayes (NB) classifier as its accuracy is about 6% higher than NB. Furthermore, the results indicate that there are positive correlations between the star-rate and the number of audiences, which can be regarded as the box-office success of a movie. The study also shows that there is the mild, positive correlation between the sentiment scores estimated by the classifier and the number of audiences. To verify the applicability of the sentiment scores, an independent sample t-test was conducted. For this, the movies were divided into two groups using the average of sentiment scores. The two groups are significantly different in terms of the star-rated scores.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.21 no.1
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• pp.5-17
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• 2010

Search engines, web portal sites, online book stores are being the main stream of information network. Library and its catalog has not influenced as the way it had been to the information network any more. Thus, institutions leading the bibliographic network started to pay much attention to the web user service. This article firstly reviewed the development of the bibliographic network, next generation catalog interface and OPAC 2.0, and investigated the case of OCLC in detail. Based on the reviews, this study suggested the development plan of bibliographic network focusing on the web user service in terms of the three strategies. It is hoped that this article will be the basic study for the future of the bibliographic network and the reference for the changes and improvements of libraries and catalog services.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.184-200
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• 2013

In post-industrial society, the ability to feel and express emotion is becoming ever more important. In diverse areas of our lives such as economic, social, political and cultural activities, we are witnessing an increased application of the emotional dimension. This paper deals with the human experiences in emotional designs. Literature reviews and case analyses have been used as the main research methods. I first examine the aspects of emotional experience in designs, and then go on to analyze the components of each aspect. Emotional experience in designs has three basic aspects : (a) initially there exist user's emotional needs (b) then these emotions are delivered through design, (c) finally, emotions expressed in designs are experienced by the user. Followings are the related components for each aspect : (a) Physiological, psychological, social and cultural factors cause one to feel emotional needs. (b) Emotion is delivered either through visual symbols, experience, interaction and participation. (c) Emotion is experienced by sensing, feeling, thinking, acting and relating.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.105-113
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• 2017

Network externality can be defined as the effect that one user of a good or service has on the value of that product to other people. When a network externality is present, the value of a product or service is dependent on the number of others using it. There exist asymmetries in network externalities between the online and traditional offline marketing channels. Technological capabilities such as interactivity and real-time communications enable the creation of virtual communities. These user communities generate significant direct as well as indirect network externalities by creating added value through user ratings, reviews and feedback, which contributes to eliminate consumers' concern for buying products without the experience of 'touch and feel'. The offline channel offers much less scope for such community building, and consequently, almost no possibility for the creation of network externality. In this study, we analyze the effect of network externality on the competition between online and conventional offline marketing channels using game theory. To do this, we first set up a two-period game model to represent the competition between online and offline marketing channels under network externalities. Numerical analysis of the Nash equilibrium solutions of the game showed that the pricing strategies of online and offline channels heavily depend not only on the strength of network externality but on the relative efficiency of online channel. When the relative efficiency of online channel is high, the online channel can greatly benefit by the network externality. On the other hand, if the relative efficiency of online channel is low, the online channel may not benefit at all by the network externality.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.181-188
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• 2018

In this paper, we propose an analysis scheme of customer spending pattern using text mining. In proposed consumption pattern analysis scheme, first we analyze user's rating similarity using Pearson correlation, second we analyze user's review similarity using TF-IDF cosine similarity, third we analyze the consistency of the rating and review using Sendiwordnet. And we select the nearest neighbors using rating similarity and review similarity, and provide the recommended list that is proper with consumption pattern. The precision of recommended list are 0.79 for the Pearson correlation, 0.73 for the TF-IDF, and 0.82 for the proposed consumption pattern. That is, the proposed consumption pattern analysis scheme can more accurately analyze consumption pattern because it uses both quantitative rating and qualitative reviews of consumers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.443-449
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• 2017

Opened platform is called that anybody can be a producer and consumer in some platform. And many opened platforms are using in various area such as general goods, smart phone application and contents. In this paper, we will propose the opened platform system for the problems for evaluation the level of learners. Any user can register problems as public or private-type in this system and use them. So our proposed system has the advantage in selecting the high quality problems by continuous reviews about that even after they have been registered. Proposed system has three different modules such as submit, evaluate and produce problems modules. A user can submit various kind of problems in the submit module. The evaluation module is a module that allows the user who is not the problem registrant to evaluate the registered problem. The production module can use the registered problems for online and offline evaluation.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.2
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• pp.35-46
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• 2008

This research developed a strategy for mobile banking services based on the important factors deduced from quality assessment of mobile banking service that is experiencing rapid growth of user. SERVQUAL model and importance-performance tool were used. First, SERVQUAL model uses the important factors of mobile banking service selected from literature reviews. As a result, four dimensions that affect user satisfaction are found; assurance, customer orientation, tangibility, and reliability. Second, importance-performance analysis is to develop the strategy using the four factors. The final results revealed that assurance dimension had the strongest influence on user satisfaction. Assurance dimension of high expectation and yet low real performance needs immediate improvement. Customer orientation dimension of low expectation and performance should be reconsidered definition of satisfaction. On the other hand, tangibility dimension of higher performance than expectation is simply to maintain current level. Reliability dimension of high expectation and performance is recommended consistent management.

• Fashion & Textile Research Journal
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• v.21 no.3
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• pp.300-307
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• 2019

This study develops a user centered outdoor jacket capable of energy harvesting based on consumer needs. Jackets are designed for typical outdoor activities such as hiking, trekking, and climbing, integrated with an energy harvesting module that can generate electric power from arm swing in outdoor and daily life walking. Textile based energy generators developed by the previous research of Lee & Roh (2018) were used. A prototype was created based on the arm swing motion experiment for location options and energy harvesting system functions, the simulation by the design sketch, and evaluation of the wearing test by experts. In-depth interviews were later conducted for the prototype with 10 outdoor experts to derive the optimal location of an energy harvesting system in three ways, and the prototype was revised to 5 styles that reflected reviews by experts on function and appearance. Research indicated that the energy harvesting jacket design signifies a user-centered design based on expert interviews and usability evaluation as well as previous research on energy generation and storage device. The jacket is convenient because it combines an energy generator in an optimal position to maximize energy generation with a storage and charging device that can be inserted into various position options for accessibility.