• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2004.11a
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• pp.85-88
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• 2004

본 논문에서는 PC 기반 지상파 DMB(Terrestrial Digital Multimedia Broadcasting, T-DMB) 수신기를 위한 대화형 방송 수신 SW 구현에 대해 설명한다. T-DMB 표준에 의하면, MPEG-4 BIFS(Binary Format for Scene)를 옵션으로 사용한 수 있게 되어 있는데, 이를 이용하면, 여러 가지 형태의 대화형 방송 기능을 실현할 수 있다. 본 논문에서는 이러한 BIFS 데이터가 포함된 비트스트림을 수신하여 이를 복호한 후, 화면에 동영상과 함께 디스플레이 하는 대화형 방송 수신 기능을 구현하였다. 또한 이를 활용하여 쉽게 구현할 수 있는, 화면상의 클릭 가능한 객체, 즉 "핫 스팟(hot-spot)"을 이용한 대화형 방송 시나리오와 예제 구현에 대해 설명한다.

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

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.1-11
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• 2018

Recently, the volume of online shopping market continues to be fast-growing, that is important to provide customized service based on customer behavior evaluation analysis. The existing systems only provide analysis data on the profiles and behaviors of the consumers, and there is a limit to the processing in real time due to disk based mining. There are problems of accuracy and system performance problems to apply existing systems to web services that require real-time processing and analysis. Therefore, The system proposed in this paper analyzes the web click log streams generated in real time to calculate the concentration level of specific products and finds interested customers which are likely to purchase the products, and provides and intensive promotions to interested customers. And we verify the efficiency and accuracy of the proposed system.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.465-470
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• 2004

Web Information Predictive Systems have the restriction such as they need users profiles and visible feedback information for obtaining the necessary information. For overcoming this restrict, this study designed and implemented Dynamic Web Information Predictive System using Ensemble Support Vector Machine to be able to predict the web information and provide the relevant information every user needs most by click stream data and user feedback information, which have some clues based on the data. The result of performance test using Dynamic Web Information Predictive System using Ensemble Support Vector Machine against the existing Web Information Predictive System has preyed that this study s method is an excellence solution.

• The KIPS Transactions:PartD
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• v.17D no.4
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• pp.253-258
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• 2010

Traditional frequent pattern mining considers equal profit/weight value of every item. Weighted Frequent Pattern (WFP) mining becomes an important research issue in data mining and knowledge discovery by considering different weights for different items. Existing algorithms in this area are based on fixed weight. But in our real world scenarios the price/weight/importance of a pattern may vary frequently due to some unavoidable situations. Tracking these dynamic changes is very necessary in different application area such as retail market basket data analysis and web click stream management. In this paper, we propose a novel concept of dynamic weight and an algorithm DWFPM (dynamic weighted frequent pattern mining). Our algorithm can handle the situation where price/weight of a pattern may vary dynamically. It scans the database exactly once and also eligible for real time data processing. To our knowledge, this is the first research work to mine weighted frequent patterns using dynamic weights. Extensive performance analyses show that our algorithm is very efficient and scalable for WFP mining using dynamic weights.

• Information Systems Review
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• v.20 no.4
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• pp.59-78
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• 2018

With the advent of the various device types and marketing communication, customer's search and purchase behavior have become more complex and segmented. However, extant research on multichannel marketing effects of the purchase funnel has not reflected the specific features of device User Interface (UI) and User Experience (UX). In this study, we analyzed the marketing channel effects of multi-device shoppers using a unique click stream dataset from global online retailers. We examined device types that activate online shopping and compared the differences between marketing channels that promote visits. In addition, we estimated the direct and indirect effects on visits and purchase revenue through customer's accumulated experience and channel conversions. The findings indicate that the same customer selects a different marketing channel according to the device selection. These results can help retailers gain a better understanding of customers' decision-making process in multi-marketing channel environment and devise the optimal strategy taking into account various device types. Our empirical analyses yield business implications based on the significant results from global big data analytics and contribute academically meaningful theoretical framework using an economic model. We also provide strategic insights attributed to the practical value of an online marketing manager.

• Journal of Broadcast Engineering
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• v.10 no.4 s.29
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• pp.474-487
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• 2005

T-DMB (Terrestrial-Digital Multimedia Broadcasting) adopted MPEG-4 BIFS (Binary Format for Scene) Core2D scene description profile and graphics profile as the standard of video associated data service. By using BIFS, we can support to overlay objects, i.e. text, stationary image, circle, polygon, etc., on the main display of receiving end according to the properties designated in broadcasting side and to make clickable buttons and website links on desired objects. Therefore, a variety of interactive data services can be served by BIFS. In this paper, we implement real-time video associated data service system far T-DMB. Our developing system places emphasis on real-time data service by user operation and on inter-working and stability with our previously developed video encoder. Our system consists of BIFS Real-time System, Automatic Stream Control System and Receiving Monitoring System. Basic functions of our system are designed to reflect T-DMB programs and characteristics of program production environment as a top priority. Our developed system was used in BIFS trial service via KBS T-DMB, it is supposed to be used in T-DMB main service after improvement process such as intensifying system stability.