• Journal of Broadcast Engineering
• /
• v.24 no.3
• /
• pp.515-526
• /
• 2019

In the real world, the user's preference for a particular product is determined by many factors besides the quality of the product. The reflection of these external factors was very difficult because of various fundamental problems including lack of data. However, access to external factors has become easier as the infrastructure for public data is opened and the availability of evaluation platforms with diverse and vast amounts of data. In accordance with these changes, this paper proposes a recommendation system structure that can reflect the collectable factors that affect user's preference, and we try to observe the influence of actual influencing factors on preference by applying case. The structure of the proposed system can be divided into a process of selecting and extracting influencing factors, a process of supplementing insufficient data using sentence analysis, and finally a process of combining and merging user's evaluation data and influencing factors. We also propose a validation process that can determine the appropriateness of the setting of the structural variables such as the selection of the influence factors through comparison between the result group of the proposed system and the actual user preference group.

• Journal of Korean Library and Information Science Society
• /
• v.53 no.2
• /
• pp.95-115
• /
• 2022

The purpose of this study is to transform the sub-categorization terms of the National Science and Technology Standards Classification System into technical keywords by applying a machine learning algorithm. For this purpose, AttentionMeSH was used as a learning algorithm suitable for topic word recommendation. For source data, four-year research status files from 2017 to 2020, refined by the Korea Institute of Science and Technology Planning and Evaluation, were used. For learning, four attributes that well express the research content were used: task name, research goal, research abstract, and expected effect. As a result, it was confirmed that the result of MiF 0.6377 was derived when the threshold was 0.5. In order to utilize machine learning in actual work in the future and to secure technical keywords, it is expected that it will be necessary to establish a term management system and secure data of various attributes.

• Information Systems Review
• /
• v.22 no.4
• /
• pp.75-92
• /
• 2020

As population and generation structures change, more and more customers tend to avoid facing relation due to the development of information technology and spread of smart phones. This phenomenon consists with efficiency and immediacy, which are the consumption patterns of modern customers who are used to information technology, so offline network-oriented distribution companies actively try to switch their sales and services to untact patterns. Recently, untact services are boosted in various fields, but beauty products are not easy to be recommended through untact services due to many options depending on skin types and conditions. There have been many studies on recommendations and development of recommendation systems in the online beauty field, but most of them are the ones that develop recommendation algorithm using survey or social data. In other words, there were not enough studies that classify segments based on user information such as skin types and product preference. Therefore, this study classifies customer segments using machine learning technique K-prototypesalgorithm based on customer information and search log data of mobile application, which is one of untact services in the beauty field, based on which, untact marketing strategy is suggested. This study expands the scope of the previous literature by classifying customer segments using the machine learning technique. This study is practically meaningful in that it classifies customer segments by reflecting new consumption trend of untact service, and based on this, it suggests a specific plan that can be used in untact services of the beauty field.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.12
• /
• pp.1154-1164
• /
• 2010

As an useful application in broadcasting services, the targeting service has been mainly studied to improve the service satisfaction and user usage in various media service environments based on user profile, preferences, and usage history. Targeting service is expanding its domain from broadcasting contents to interstitial contents and from fixed TV devices to mobile devices. Service data also include advertisement data, coupon, and information about media contents as well as simple broadcasting data. In this paper, the targeting data service is designed and implemented on articles, advertisement and broadcasting information on the basis of the user information. To adapt this to web-based media contents, information on user profile, preferences, and usage history is newly defined on the basis of the user metadata developed in TV-Anytime Forum and the user information defined in OpenSocial. The targeting data service is implemented to generate user preferences information and usage history pattern based on the similarity among user preference, contents information, and usage history. Based on performance evaluation, we prove that the proposed targeting data service is effectively applicable to web-based media contents as well as broadcasting service.

• Journal of Digital Contents Society
• /
• v.18 no.3
• /
• pp.567-575
• /
• 2017

Location-based services play an important role in many applications such as disaster warning systems and recommendation systems. These applications often require not only location information (e.g., name, latitude, longitude, etc.) but also the impact of events (e.g., earthquake, typhoon, etc.) on locations. Recently, to provide the impact of an event on a location, how to calculate location trustiness by using multimodal information such as earthquake information and disaster sensor data is researched. In the previous approach, the linear decrement of impact value of an event is applied to obtain the location trustiness of a specific location. In this paper, we propose a new approach to enrich location trustiness, that is, the impact of an event on a location, by using social media information additionally. Firstly, we design a collecting system for earthquake information and social media data. Secondly, we present an approach of location trustiness calculation based on earthquake information. Finally, we propose a new approach to enrich location trustiness by augmenting the trustiness in spatially distributed manner based on social media.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.8
• /
• pp.315-320
• /
• 2015

The purposed of this research is to develop multimedia content usage analysis service platform. In the proposed platform, the content gazing behaviors of the users are monitored and profiled in real-time and a set of quantifiable metrics is provided. These metrics are used to determine the closeness of the users' behavior from the intent set by the provider. Based on the evaluation, it is possible to assess the effectiveness of the contents themselves as well. The content usage assessment is accomplished by utilizing the intention flow and the intent weight, which are embedded into the content by the content provider. Proposed methodology can be effectively applied and used in various application domains such as in education and in commercial advertisements.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.11A
• /
• pp.1117-1123
• /
• 2008

Applications for mobile multimedia are testing the performance limits of present day CPUs with variety. However, hardwired solutions are inflexible and expensive to develop. CPUs with flexibility have limitation of performance. So, the requirement for both ASIC-like performance and CPU-like flexibility has led to reconfigurable processor. Mobile systems require low power and high performance concurrently. In this paper, we propose reconfigurable processor for mobile multimedia with high energy efficiency. Reconfigurable processor with 121MOPS/mW is developed by 130nm CMOS technology. And the processor was simulated for energy efficiency with 539MOPS/mW by 90nm CMOS technology and effective use of instructions. And we tested its applications for multimedia field. We tested the case of inverse MDCT for MP3 and DF for MPEG4 and ME for H.264.

• Journal of Korea Multimedia Society
• /
• v.18 no.9
• /
• pp.1068-1082
• /
• 2015

Due to the rapid advancement of the mobile technology, smart phones have been widely used in the current society. This lead to an easier way to retrieve video contents using web and mobile services. However, it is not a trivial problem to retrieve particular video contents based on users' specific preferences. The current movie recommendation system is based on the users' preference information. However, this system does not consider any emotional means or perspectives in each movie, which results in the dissatisfaction of user's emotional requirements. In order to address users' preferences and emotional requirements, this research proposes a movie recommendation technology to represent a movie's emotion and its associations. The proposed approach contains the development of emotion ontology by representing the relationship between the emotion and the concepts which cause emotional effects. Based on the current movie metadata ontology, this research also developed movie-emotion ontology based on the representation of the metadata related to the emotion. The proposed movie recommendation method recommends the movie by using movie-emotion ontology based on the emotion knowledge. Using this proposed approach, the user will be able to get the list of movies based on their preferences and emotional requirements.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2019.11a
• /
• pp.71-72
• /
• 2019

최근 공공안전 분야에서는 국민의 위험상황을 분석하여 선제적으로 예측을 하여 국민의 안전을 보장하기 위한 요구사항이 대두대고 있다. 또한 스마트폰 및 스마트워치와 같은 고성능 모바일 단말 기기들의 대중화로 인해 해당 기기들에 부착된 다양한 센서 데이터들을 융복합하여 분석할 경우, 수집한 센서 데이터의 잠재적 가치를 안전보장 측면에서 사용할 수 있는 장점이 있다. 본 논문에서는 대인, 대물, 장소에 해당하는 로그 데이터들을 융복합 분석하여 보호대상자의 안전을 지원하는 다중로그 플랫폼 기반 이동경로 분석 기법을 제안한다. 다중로그 플랫폼에서 수집하는 보호대상자의 이동 경로 궤적을 활용하여 과거에 축적된 이동경로 패턴과 비교를 통해 현재 경로가 평소에 이용하던 경로와의 유사도를 추천하게 된다. 해당 이동 경로 분석 시스템은 위치기반 멀티모달 센서 데이터를 융복합 하여 보호대상자의 안전을 보장하는데 기여 할 것으로 예상된다.

• Journal of Korea Multimedia Society
• /
• v.19 no.11
• /
• pp.1878-1890
• /
• 2016

Web 2.0 has features produced the content through the user of the participation and share. The content production activities have became active since social network service appear. The social bookmark, one of social network service, is service that lets users to store useful content and share bookmarked contents between personal users. Unlike Internet search engines such as Google and Naver, the content stored on social bookmark is searched based on tag keyword information and unnecessary information can be excluded. Social bookmark can make users access to selected content. However, quick access to content that users want is difficult job because of the user of the participation and share. Our paper suggests a method recommending search word to be able to access quickly to content. A method is suggested by using Collaborative Filtering and Jaccard similarity coefficient. The performance of suggested system is verified with experiments that compare by 'Delicious' and "Feeltering' with our system.