• Journal of Information Processing Systems
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• v.8 no.4
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• pp.721-738
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• 2012

The Internet has become an increasingly important source for finding the right employees, so more and more companies post their job openings on the Web. The large amount and dynamic nature of career recruiting information causes information overload problems for job seekers. To assist Internet users in searching for the right job, a range of research and commercial systems were developed over the past 10 years. Surprisingly, the majority of existing job search systems support just one, rarely two ways of information access. In contrast, our work focused on exploring a value of comprehensive access to job information in a single system (i.e., a system which supports multiple ways). We designed Proactive, a recommendation system providing comprehensive and personalized information access. To assist the varied needs of users, Proactive has four information retrieval methods - a navigable list of jobs, keyword-based search, implicit preference-based recommendations, and explicit preference-based recommendations. This paper introduces the Proactive and reports the results of a study focusing on the experimental evaluation of these methods. The goal of the study was to assess whether all of the methods are necessary for users to find relevant jobs and to what extent different methods can meet different users' information requirements.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.25-34
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• 2017

With the recent spread of smartphones and the introduction of web services, online users can access large-scale content regardless of time or place. However, users have had trouble finding the content they wanted among large-scale content. To solve this problem, user modeling and content recommendation system have been actively studied in various fields. However, in spite of active changes in senior groups according to the changes in information environment, research on user modeling and content recommendation system focused on senior groups are insufficient. In this paper, we propose a method of modeling smart senior based on their preference, and further develop a smart senior classification model using machine learning methods. As a result, we can not only grasp the preferences of smart seniors, but also develop a smart senior classification model, which is the foundation for the research of a recommendation system which will provide the activities and contents most suitable for senior groups.

• Journal of the Korean Society for Library and Information Science
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• v.39 no.3
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• pp.75-91
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• 2005

The popularization of the internet has produced an explosion in amount of the information. The importance of web personalization is being more and more increased. The personalization is realized by learning user's interest. User's interest is changing continuously and rapidly. We use user's profile to represent user's interest. User's profile is updated to reflect the change of user's interest. In this paper we present an adaptive learning algorithm that can be used to reflect user's interest that is changing with time. We propose the User's profile model. With this profile user's interest is learned based on user's feedback. This approach has applied to develop hybrid recommendation system.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.1-15
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• 2006

Currently the mobile web service is growing with a tremendous speed and mobile contents are spreading extensively. However, it is hard to search what the user wants because of some limitations of cellular phones. And the music is the most popular content, but many users experience frustrations to search their desired music. To solve these problems, this research proposes a hybrid recommendation system, MOBICORS-music (MOBIle COntents Recommender System for Music). Basically it follows the procedure of Collaborative Filtering (CF) system, but it uses Contents-Based (CB) data representation for neighborhood formation and recommendation of new music. Based on this data representation, MOBICORS-music solves the new item ramp-up problem and results better performance than existing CF systems. The procedure of MOBICORS-music is explained step by step with an illustrative example.

• Journal of Digital Convergence
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• v.11 no.1
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• pp.249-254
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• 2013

The number of channels are increased into several hundreds of channels when coming out the digital broadcasting era. In this environment, viewers searching for programs will be very difficult to do. In addition, recent popularization of smart devices are receiving the services that they previously had not been given to. A TV program recommended a system that has been studied as a way to solve these problems. However, most studies have been studied in most web-based research results when applied to broadcast TV for TV program recommendations. In particular, the combination of the current members who watch TV are not considered. In this paper, the environment and TV viewers are considering a combination of the members of the TV program's recommended system proposal. In order to make a group deal successful, we employ the face recognition.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.43-48
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• 2008

And this study intends to discuss especially the one using emotional filter among various information processing methods. The existing music recommendation service on the web has a weak point that it makes the user feel bored by recommending songs only with similar feeling of the same genre, because music is classified by tune, melody, atmosphere and genre before recommendation. The service using emotion filter, suggested in this study, recommends the song and lyrics appropriate to the current emotional state of the user by abstracting emotional words that could reflect the sensitivity of human and then search the words within lyrics to match in order to overcome the weak point of the existing service. This study starts where the current emotional status for the user is being input. As for the range to choose, there are the seven representatives of emotion which are, love, separation, joy, sorrow-gloom, happiness-lonesome, and anger. As the service receives input of user's emotion, it matches the emotional words appropriate for the emotion input with the lyrics, and ranks the lyrics in the order of priority, so that it recommends the song and it lyrics to the user.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.31-36
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• 2019

A chatbot is an important area of mobile service, which understands informal data of a user as a conversational form and provides a customized service information for user. However, there is still a lack of a service way to fully understand the user's natural language typed query dialogue. Therefore, in this paper, we extract meaningful words, such a region, a food category, and a restaurant name from user's dialogue sentences for recommending a restaurant. and by comparing the extracted words against the contents of the knowledge database that is built from the hashtag for recommending a restaurant in SNS, and provides user target information having statistically much the word-similarity. In order to evaluate the performance of the restaurant recommendation chatbot system implemented in this paper, we measured the accessibility of various user query information by constructing a web-based mobile environment. As a results by comparing a previous similar system, our chabot is reduced by 37.2% and 73.3% with respect to the touch-count and the cutaway-count respectively.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.407-413
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• 2022

Existing clothing recommendation systems remain at the level of showing appropriate photos when a user selects a type of clothing he or she likes after entering his or her own body size or body size. When a user purchases clothing using such recommendation systems, there are many cases in which it does not fit or does not fit the user's body size. In this study, to solve these problems of existing clothing recommendation systems, a system was implemented in which the user receives not only size but also skin tone and recommends clothing suitable for the user's body size as well as skin tone. In this system, clothing size information obtained through web crawling was periodically stored in a database for eight male tops to recommend clothing, and the entire pixel of the clothing image was analyzed to extract color text values. In order to confirm the performance of this system, a survey was conducted on 100 male college students, and the satisfaction level was 70%. Most of the reasons for not being satisfied are that the recommended clothing is limited, so it is judged that it is necessary to expand the target clothing in the future.

• The Journal of Society for e-Business Studies
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• v.9 no.3
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• pp.155-167
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• 2004

At this time, the two main techniques for achieving web personalization assistant systems generally concern direct manipulation and software agents. While both direct manipulation and software agents are intended for permitting user to complete tasks rapidly, efficiently, and easily, their methodologies are different. The central debate involving these web personalization techniques originates from the amount of control that each allows to, or holds back from, the users. Direct manipulation can provide users with comprehensibel, predictable and controllable user interfaces that give them a feeling of accomplishnent and responsibility. On the other hand, the intelligent software components, the agents, can assist users with artificial intelligence by monitoring or retrieving personal histories or behaviors. In this empirical study, two web personalization assistant systems are evaluated. One of them, WebPersonalizer, is an agent based user personalization tool; the other, AntWorld, is a collaborative recommendation tool which provides direct manipulation interfaces. Through this empirical study, we have focused on two different paradigms as web personalization assistant systems : direct manipulation and software agents. Each approach has its own advantages and disadvantages. We also provide the experimental result that is worth referring for developers of electronic commerce system and suggest the methodologies for conveniently retrieving necessary information based on their personal needs.

• Asian Oncology Nursing
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• v.5 no.1
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• pp.11-21
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• 2005

The purpose of this study were to develop an web-based education program for Lung cancer patients and to test its effects on patients' self-care knowledge, compliance to medical regimen, nutrition status and pain. The program was developed by the following process: first, Lung cancer patients demand on the web-based program was investigated. and second, the program was developed with the help of various reference books and then validation of experts group. last, educations effects on the patients is evaluated and compared the differences in self-care knowledge, compliance to medical regimen, nutrition status and pain between on experimental group and a control group on before discharge 1day and 3weeks after. SPSS/Win 11.0 program was used for data analysis. It was proven with $x^2$ test and t-test, and Pearson Correlation coefficient, and Chronbach's alpha coefficient were done for the reliability of measuring instruments. 1. The summary of the Program development is as follows. The program is based on patients' questionnaire and reference material and is made for users friendly. Not only Bigger font size and bright colors but also illustrations or pictures were adopted to help enhance patients' understanding. 2. The summary of the study results is as follows. 1) Compared with control group, the web-based educated experimental group showed a statistical significant difference on self-care knowledge, Especially disease, radiation treatment, medication & analgesics, chemotherapy side effect, but there was no significant difference in the field of chemotherapy, in the fields of operation, diet & general knowledge. 2) Compared with control group, the web-based educated experimental group showed a statistical significant difference on compliance to medical regimen, especially in the field of follow up care, everyday life, diet, but there was no significant difference in the field of medication, exercise. 3) Compared with control group, web-based educated experimental group showed no significant difference in nutrition status, but partially significant difference in body weight. 4) Compared with control group, the web-based educated experimental group showed no significant difference in pain level. 5) The significantly positive correalation self-care knowledge with the compliance to medical regimen. 6) Users satisfaction with the web-based education program of the contents quality, the level of recommendation to others, content layout, medical information quality, but interesting got a low mark.