• Journal of the Korea Convergence Society
• /
• v.9 no.12
• /
• pp.25-32
• /
• 2018

In the massive online fashion market, it is not easy for consumers to find the fashion style they want by keyword search for their preferred style. It can be resolved into consumer needs based fashion recommendation. Most of the existing online shopping sites have collected cumtomer's preference style using the online quastionnair. In this paper, we propose a simple but effective novel model that resolve the traditional method in fashion profiling for consumer's preference style and needs using implicit profiling method. In addition, we proposed a learning model that reflects the characteristics of the images itself through the deep learning-based intelligent preferred fashion model learned from the collected data. We show that the proposed model gave meaningful results through the qualitative evaluation.

• Design Convergence Study
• /
• v.14 no.5
• /
• pp.47-56
• /
• 2015

People often use haptic experience as a basis for their preference decisions and value judgments, assuming that haptic experience with a product results from the properties of the products. However, research has suggested that unplanned haptic experience, which does not arise from the properties of the product itself, can also influence people's preference and value evaluation (Ackerman, Nocera, & Bargh, 2010). In this study, in order to verify (1) if such unplanned or accidental haptic experience changes user's cognitive tendency and (2) if accidental haptic experience leads to misattribution of the cause of haptic experience, two hypotheses were suggested and empirically investigated. Participants of the experiment were exposed to certain products on a display of a tablet PC and asked to decide on the maximum price they were willing to pay for each product. The products displayed on the screen were made up of either soft material or hard material. Results of the experiment revealed that accidental haptic experience had an effect on participants' value evaluation of products via altering their cognitive inclinations. Possible applicability of accidental haptic experiences that occur in various situations were discussed.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.36 no.4
• /
• pp.43-61
• /
• 2011

We first develop a value ecosystem framework to model the SDP(Service Delivery Process) of web services. Since the web service has been evolving from the basic web architecture (e.g., traditional world wide web) to a prosuming platform based on virtualization technologies, the proposed framework of the value ecosystem focuses on capturing the key characteristics of SDP in each type of web services. Even though they share the basic elements such as PP(Platform Provider), CA(Customization Agency) and user group, the SDP in the traditional web services (so-called Web1.0 in this paper) is quite different from the most recent one (so-called Web2.0). In our value ecosystem, users are uniformly distributed over (0, ${\Delta}$), where ${\Delta}$��represents the variety level of users' preference on the web service level. PP and CA provide a standard level of web service(s) and prosuming service package, respectively. CA in Web1.0 presents a standard customization package($s_a$) at flat rate c, whereas PP and CA collaborate and provide customization service with a usage-based scheme. We employ a multi-stage game model to analyze and compare the SDPs in Web1.0 and Web2.0. Our findings through analysis and numerical simulations are as follows. First, the user group is consecutively segmented, and the pattern of the segmentations varies across Web1.0 and Web2.0. The standardized service level s (from PP) is higher in Web1.0, whereas the amount of information created in the value ecosystem is bigger in Web2.0. This indicates the role of CA would be increasingly critical in Web2.0: in particular, for fulfilling the needs of prosuming and service customization.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.1
• /
• pp.104-109
• /
• 2005

Context-awareness is an important element that can provide service of good quality according to users' surrounding environment and status in ubiquitous computing environment. Information gathering tools for context-awareness use small size mobile devices which have easy movement and a mobile agent in mobile device. Now, Mobile agents are consuming much times and expense to collect and recognize each users' context information. Therefore, needs research about structure for users' context information awareness in early time to reduce mobile agent's load. This paper proposes a P2P mobile agent structure that mikes filtering techniques and a P2P agent in mobile agent. The proposed structure analyzes each user's context information in same area, and groups users who have similar preference degree. Grouped users share information using a P2P mobile agent. Also this structure observes and learns to continue on users' action and service, and measures new interrelation.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.2
• /
• pp.108-117
• /
• 2009

The South Korean government is looking for a solution to the ever-growing problems of traffic congestion, and surging international oil prices: the use of the humble bicycle to get to places. However, Many people feel inconvenient using bicycle because of the insufficient bicycle infrastructure and lack of the safety and connectivity between existing pathways. In this study, bicycle level of service model using ordered probit model is developed considering safety, convenience, connectivity, and factors that affect bicycle LOS. The ordered probit model would be recommended for the research which relates in choice, preference and strength etc. Bicycle level of service criteria is calculated by applying this model reflecting bicyclist's point of view. The model which develops from this research which accomplishes a bicycle level of service evaluation and represent alternative solution to encourage bicyclist. It is believed that the proposed model would be greatly utilized in bicycle network planning, bicycle road and facility alternatives testing, projects funding priority.

• Journal of Digital Contents Society
• /
• v.18 no.4
• /
• pp.707-712
• /
• 2017

As the amount of data increases exponentially, the recommender system is attracting interest in various industries such as movies, books, and music, and is being studied. The recommendation system aims to propose an appropriate item to the user based on the user's past preference and click stream. Typical examples include Netflix's movie recommendation system and Amazon's book recommendation system. Previous studies can be categorized into three types: collaborative filtering, content-based recommendation, and hybrid recommendation. However, existing recommendation systems have disadvantages such as sparsity, cold start, and scalability problems. To improve these shortcomings and to develop a more accurate recommendation system, we have designed a recommendation system as a factorization machine using actual online product purchase data.

• Journal of KIISE:Software and Applications
• /
• v.31 no.3
• /
• pp.332-342
• /
• 2004

With the explosive growth of information in our real life, information filtering is quickly becoming a popular technique for reducing information overload. Information filtering technique is divided into two categories: content-based filtering and collaborative filtering (or social filtering). Content-based filtering selects the information based on contents; while collaborative filtering combines the opinions of other persons to make a prediction for the target user. In this paper, we describe a new filtering approach that seamlessly combines content-based filtering and collaborative filtering to take advantages from both of them, where a technique using user profiles efficiently on the collaborative filtering framework is introduced to predict a user's preference. The proposed approach is experimentally evaluated and compared to conventional filtering. Our experiments showed that the proposed approach not only achieved significant improvement in prediction quality, but also dealt with new users well.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.7B
• /
• pp.619-631
• /
• 2006

With the advent of ubiquitous computing environments, it has become increasingly important for applications to take full advantage of context information, such as the user's location, to offer greater services to the user without any explicit request. In this paper, we propose context-aware active services on the basis of CAMUS (Context-Aware Middleware for URC Systems). CAMUS is a middleware for providing context-aware applications with development and execution methodology. Accordingly, the applications developed by CAMUS respond in a timely fashion to contexts. To evaluate, we apply proposed active services to TV application domain. Therefore, we implement and experiment the TV contents recommendation service agent, control service agent and TV task based on CAMUS. The context-aware TV task is to recommend programs and control of TV according to user preference, location and voice commands.

• Journal of the Korean Society of Costume
• /
• v.56 no.6 s.105
• /
• pp.58-71
• /
• 2006

This research is aimed to develop the functional clothing designs for disabled women in the manner of investigating design preferences among them by means of questionnaire and interview with 150 disabled women as respondents and interviewees. The findings of this research are summarized as follows: 1. Regarding satisfaction with ready-made clothes, the respondents answered 'very satisfied' (1.6%), 'usually satisfied' (14.1%), 'moderate' (20.3%) and 'unsatisfied' (53.1%), suggesting that they had been generally unsatisfied with ready-made clothes. 2. There were more disabled women preferring to ready-made clothes with one-grade bigger (loose.) size than the actual one (53.1%) instead of completely fitted size (43.8%) when they purchased such clothes. This result indicates that they prefer to ready-made clothes with bigger size than the actual one because most of such clothes are made up of non-elastic materials which may be unfavorable for wearer's activities. 3. It was found that primarily worn upper garment among them was T-shirt (59.4%). The reason may be that T-shirt is favorable for using prosthesis and orthotics such as wheelchair, walking stick and crutches thanks to its remarkably high activity as well as simple to maintain, compared with other kinds of upper garments. 4. Regarding preferences to functional clothing designs, the primarily worn lower garment among them was trousers (85.9%); the reason was easiness to move. The main reasons of avoiding to wear a skirt included 'difficult to move' (40.6%) and 'exposed disabled region' (30.3%). Accordingly, functional clothing for disabled women should be developed in consideration for their individual characteristics of disability associated with the disabled region such as wheelchair user, crutch user or brace user, In addition, the designs should be made so that they are not different from those for non-disabled people.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.6
• /
• pp.643-648
• /
• 2003

In order to provide efficient retrieving results for user query on the web environment, the various searching algorithms have developed and considered user's preference and convenience. However, the searching algorithms are developed on the horizontal and non hierarchical web environment in general and could not apply to the complex hierarchical and functional web environments such like the enterprise network. In this paper, we purpose the multi-agent based web mining system which can provide the efficient mining results to the user on the special web environment. For doing this, we suggest the network model with the hierarchical web environment and model the multi agent based web mining system which has four corporation agents and fourteen process modules. Then, we explain the detailed functions of each agent considered the hierarchical environment according to the module. Especially, we purpose the new merging agent and improved ranking algorithm by using the graph theory.