Jo, Jung-Heum;Chung, Yong-Taek;Choi, Seong-Wook;Ok, Changsoo
Journal of Korean Society of Industrial and Systems Engineering
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v.41
no.4
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pp.131-137
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2018
People write reviews of numerous products or services on the Internet, in their blogs or community bulletin boards. These unstructured data contain important emotions and opinions about the author's product or service, which can provide important information for future product design or marketing. However, this text-based information cannot be evaluated quantitatively, and thus they are difficult to apply to mathematical models or optimization problems for product design and improvement. Therefore, this study proposes a method to quantitatively extract user's opinion or preference about a specific product or service by utilizing a lot of text-based information existing on the Internet or online. The extracted unstructured text information is decomposed into basic unit words, and positive rate is evaluated by using existing emotional dictionaries and additional lists proposed in this study. This can be a way to effectively utilize unstructured text data, which is being generated and stored in vast quantities, in product or service design. Finally, to verify the effectiveness of the proposed method, a case study was conducted using movie review data retrieved from a portal website. By comparing the positive rates calculated by the proposed framework with user ratings for movies, a guideline on text mining based evaluation of unstructured data is provided.
Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.
Journal of the Korea Academia-Industrial cooperation Society
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v.16
no.10
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pp.6475-6482
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2015
The purpose of the study was two folded: to examine whether form-focused instruction (FFI) with corrective feedback (CF) is effective for the acquisition of the target linguistic forms and to find out the extent to which of the students' perceptions as well as their attitudes towards English instruction that they received. Tests and questionnaires were implemented to 122 Korean EFL students from eight classes enrolled in an English communication course. They were randomly assigned to three groups: the input-based group, who received typographical input enhancement materials, so-called the TIE group, the output-based group, who performed dictogloss tasks, so-called the DICT group, and the control group (CG). The data analysis was made on both tests and questionnaires by using SPSS 21.0 for Windows. The study found that different types of FFI with CF contributed to the improvement of students' grammatical knowledge and both the TIE and DICT task group students positively changed their perceptions and understanding as well as their attitudes towards the English instruction given, and students in all groups preferred pair work activities. In addition, most of the TIE and DICT students showed their interest and satisfaction with English class, whereas the CG group students did not. Based on the findings, this study suggested that well-planned and properly-chosen FFI in the form of pair work activities should be applied in classrooms with consideration of students' instructional preference in Korean EFL contextual settings.
Character images for the background screen of cell phones are one of the fast growing sectors of the mobile content market. However, character image buyers currently experience tremendous difficulties in searching for desired images due to the awkward image search process. Content-based image retrieval (CBIR) widely used for image retrieval could be a good candidate as a solution to this problem, but it needs to overcome the limitation of the mobile Internet environment where an initial query set (IQS) cannot be easily provided as in the PC-based environment. We propose a new approach, IQS-AutoGen, which automatically generates an initial query set for CBIR on the mobile Internet. The approach applies the collaborative filtering (CF), a well-known recommendation technique, to the CBIR process by using users' preference information collected during the relevance feedback process of CBIR. The results of the experiment using a PC-based prototype system show that the proposed approach successfully satisfies the initial query requirement of CBIR in the mobile Internet environment, thereby outperforming the current image search process on the mobile Internet.
Objectives: This study was conducted to examine the preferences and needs of typical Korean females adults for food and nutrition information provided by the mass media. Methods: A total of 343 females (77 in their 20s, 85 in their 30s, 88 in their 40s and 93 in their 50s) residing in the Seoul/Gyeonggido area was surveyed on general characteristics, main sources of food and nutrition information and needs for sources and contents of nutrition information. Results: The survey showed that typical Korean females obtained knowledge of food and nutrition mainly through the Internet (30.4%) and broadcasting (29.0%). Typical Korean females were interested in 'dietary management for weight control' (21.9%), 'the prevention and treatment of disease' (20.0%), 'food safety' (16.8%), 'proper dietary habits' (14.6%), 'cookery' (11.8%), 'functional foods' (9.6%), 'restaurant details' (3.5%) and 'life-cycle-specific dietary guideline' (1.6%). Needs for food and nutrition program forms on TV were 'educational programs' (34.3%), 'documentaries' (20.8), 'expert lecture-style' (13.0%), 'entertainment programs' (11.9%), 'expert conversation' (11.4%), 'news-style' (4.6%) and 'public campaign advertisements' (4.0%). On the Internet, 38.6% of the respondents preferred to get information provided by food and nutrition-related institutions (38.6%) while 26.1% preferred webtoons for nutritional information. The favored forms in mobile applications were 'monitoring their diets' (29.5%), 'data-based texts information' (21.4%), 'experts feedback' (20.6%), 'communities' (15.1%) and 'games' (13.1%). The rates of the preference to obtain information from experts such as nutritionists and dietitians and doctorsor dietitian turned reporters increased markedly with older ages. Conclusions: Since the mass media is a main source of food and nutrition information for the general public, the effectiveness and accuracy of the information provided should be enhanced by taking the needs of the public into account. The quality of information should be improved by involving more nutrition experts.
We examined the strategies to stimulate the reflective thinking using science notebook for the improvement of problem solving ability which is one of the core skills for the future. The strategies we derived have four steps which are input, output, solving mission and reflection as my own mirror. We applied the strategies to the 6th grade class for autumn semester in order to examine the students learning process and the result. We could observe that students looked into their own learning and had a time to look back their activities in the class. We could also confirmed that science notebook would be effective to improve the problem solving as stimulating the reflective thinking. In addition, we could specify the strategy of using science notebook in the class. At a 'input' stage, students should be able to choose their own learning style as their preference and teacher need to give them proper feedback. Interaction with peers should be emphasized during the activities as 'question attack' and 'question defense' in 'output' stage and 'solving mission' stage. You should suggest the students various method to record their thought from looking back their classroom activities instead of mere writing. We also examine the students achievement from the students' notebook and Meta Cognitive Awareness test. As a result, students who had studied using science notebook showed statistically meaningful higher achievement than controlled students.
This paper presents a personalized web agent that constructs user profile which consists of user preferences on the web and recommends his/her relevant information to the user. The personalized web agent consists of monitor agent, user profile construction agent, and user profile refinement agent. The monitor agent makes a user describe his/her preferences directly and it creates the database of preference document, finally performs several keyword extraction to increase the accuracy of the DB. The user profile construction agent transforms the extracted keywords into user profile that could be confirmed and edited by the user. and the refinement agent refines user profile by recursively learning and processing user feedback. In this paper, we describe the several keyword weighting and inductive learning techniques in detail. Finally, we describe the adaptive web retrieval and push agent that perform adaptive services to the user.
Lee, Soo-Jin;Park, Su-Zanne H.;Shin, Sang-Woo;Chae, Han
The Journal of Korean Medicine
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v.29
no.1
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pp.25-38
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2008
Objectives : Integrative medicine in Korea is the 21st century-style medical practice of two orthodox medical doctrines, traditional Korean medicine and western conventional medicine, as well as complementary and alternative medicine (CAM). CAM with scientific evidence should be incorporated in undergraduate curricula for the purpose of Korean integrative medicine. Methods : Items of detailed objectives, syllabi, textbooks, instructor's experiences, and effectiveness and reason for difficulty of the CAM curriculum for undergraduate students were analyzed and the preference of CAM therapies and others were also evaluated. Results and Discussion : The effectiveness of this CAM class curriculum was high (8.0$\pm$1.4) enough to be used in other Oriental medical colleges. Development of ability for self-study was rated as 7.0$\pm$1.7 and the helpfulness for clinical use was marked as 6.8$\pm$1.9. Students preferred placebo, Ayurveda, aromatherapy, yoga, functional food, bio-feedback and homeopathy. The difficulty degree was 7.2$\pm$1.6, and the amount of content was suggested as the major reason for it. We also found that this curriculum can be a model for self-oriented study and problem-based learning. Discussions were made for the improvement of the implemented CAM curriculum, which was shown to be very effective for the achievement of Korean integrative medicine. Conclusion : We have successfully installed a CAM curriculum for undergraduate students at the College of Oriental Medicine, and it can be used in others.
Mobile spam message is a harmful factor which makes receivers to be annoyed and leads to unnecessary social cost. Unwanted junk messages flowing to a smart phone ruin main purpose of the smart work system to enhance the productivity, so we need to study on this area. In this paper, we proposed a novel spam filter on the smartphone in order to reduce computing process and improve the accuracy rate by feedback of error results to a training sample set. As the spam classifier operates on the smartphone independently with training on only user's received data, it could reflect user preference. The authorized personal computer takes on heavy works, such as preprocessing, feature selecting and training process, and the smartphone takes on light works to block junk messages. Experimental results showed reasonable accuracy rate of over 95%, and we found that the application occupied constant computing resources while running on the phone.
Rahman, Mahfuzur;Ismail, Yusof;Albaity, Mohamed;Isa, Che Ruhana
The Journal of Asian Finance, Economics and Business
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v.4
no.2
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pp.75-80
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2017
Hand phones are standard paraphernalia among university students. Factors that motivate them to own the gadget would be of interest to both the students as well as marketers. Hand phone usage is an unexamined field in academic literature, this exploratory study attempts to investigate student purchasing motives in cellular phone markets. It also intends to know the student's satisfaction with the different services and its future impact on socio economic changes. In this study, undergraduates (n=336) were requested to specify their purchase criteria of hand phone. The instrument used in the study to collect feedback from the respondents contains a combination of open-ended and scaled questions, and some background demographics. The study employed content analysis, Pearson's correlation, and t-tests as the primary tools to analyze the responses. Results show that brand was rated as the most important factor in student purchase decisions. Other factors, arranged in decreasing order of importance comprise price, product quality, features, durability, availability, promotion, and post purchase service. Brand and price correlated significantly. It is also observed that there is very little difference regarding preference between brand and price in purchasing a hand phone. Marketers may formulate suitable strategies out of the findings to promote hand phones to university undergraduates in Malaysia by emphasizing at brands and price.
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