• Title/Summary/Keyword: User data

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Routing Relevant Data to Group Mobile Users by Mining Social Trajectory Pattern

  • Cho, Hyunjeong;Park, Yourim;Lee, HyungJune
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38B no.11
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    • pp.934-936
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    • 2013
  • A routing scheme for a group of mobile users for wireless ad-hoc networks is presented. The proposed scheme mines social activity patterns from wireless traces, and exploits social user group for efficient data routing among users based on a data publish approach. Simulation results based on real-world wireless traces show that our routing scheme reduces routing cost for a large mobile user group with a factor of 1.8 compared to a baseline counterpart.

User Intention-Awareness System for Goal-oriented Context-Awareness Service

  • Lee, Jung-Eun;Yoon, Tae-Bok;Lee, Jee-Hyong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.2
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    • pp.154-158
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    • 2007
  • As the technology developed, the system is being developed as the structure that is adapted to the intelligent environment. Therefore, the existing situation information system couldn't provide satisfactory service to the user as it provides service only by the information which it received from the sensor. This paper analyzed the problems of the existing user intention awareness system and suggested user intention awareness system to provide a stable and efficient service that fits to the intention of the user compensating this. This paper has collected the behavior data based on the scenario of the sequential behavior course of the user that occurs at breakfast time in the kitchen which is the home domain environment thai is closely related to our lives. This scenario course also showed the flow that the goal intentional user intention awareness system acted that it suggested, and showed the sequential course processing the user behavior data by tables and charts.

Mobile Way-Finding Application of User Location Base (사용자 위치 기반의 모바일 길 찾기 어플리케이션)

  • Chung, Myoung-Beom;Ko, Il-Ju
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.12
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    • pp.205-214
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    • 2011
  • In this paper, we propose a mobile navigation application that allows a user to send location data to another user using the iPhone's GPS function and Mapkit framework. The GPS function of the iPhone detects the location of the first user and the Mapkit framework shows the first user location on Google Maps. If the second user requires guidance to a destination, the first user touches the record button on the proposed application to record his or her position. The first user can check his or her recorded location from the pin position on Google Maps, and he or she can then send the relevant information to the second user who wants to visit that location. The second user receives the location data and is guided to the destination easily by following the next position icon on the iPhone camera overlay or by following the pin position on Google Maps. Therefore, even if a user is traveling somewhere for the first time, the proposed application guides that user to his or her destination by receiving recorded location data from another user.

Automatic Measurement of Temperature in Real Time by Using an Internal and Data Processing System (인터넷을 이용한 원격 실시간 온도 계측 모니터 및 계측데이터 자동처리 시스템)

  • Kim, Hui-Sik;Kim, Yeong-Il;Seol, Dae-Yeon;Nam, Cheol;O, Heung-Il
    • Proceedings of the KIEE Conference
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    • 2003.11b
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    • pp.99-102
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    • 2003
  • In this paper, we have developed a system for monitoring and processing the real time sensor data in remote site through Internet. For realizing this system, measurement equipment and protocol are used to transmit the measurement data to remote server and to process measurement data. In server part, the received data from remote site sensor is converted to text or graphic charts for user. The measurement device in sensor part receives the sensor data form sensor and store the received data to its internal memory for transmitting data to server part through Internet. Also the measurement device can receive data form server. The temperature sensor is corrected to the measurement device located in laboratory and the measurement device measures temperature of laboratory which can be confirmed by user through Internet. We have developed a server program working on the Linux to store measurement data from measurement device to server memory. The program is use for SNMP(Simple Network Management Protocol) to exchange data with measurement device. Also the program changes the measurement data into text and graphic charts for user display. The program is use apache PHP program for user display and inquiry. The real time temperature measurement system can be applly for many parts of industry and living.

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User-Perspective Issue Clustering Using Multi-Layered Two-Mode Network Analysis (다계층 이원 네트워크를 활용한 사용자 관점의 이슈 클러스터링)

  • Kim, Jieun;Kim, Namgyu;Cho, Yoonho
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.93-107
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    • 2014
  • In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

Cross-Product Category User Profiling for E-Commerce Personalized Recommendation (전자상거래 개인화 추천을 위한 상품 카테고리 중립적 사용자 프로파일링)

  • Park, Soo-Hwan;Lee, Hong-Joo;Cho, Nam-Jae;Kim, Jong-Woo
    • Asia pacific journal of information systems
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    • v.16 no.3
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    • pp.159-176
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    • 2006
  • Collaborative filtering is one of the popular techniques for personalized recommendation in e-commerce. In collaborative filtering, user profiles are usually managed per product category in order to reduce data sparsity. Product diversification of Internet storefronts and multiple product category sales of e-commerce portals require cross-product category usage of user profiles in order to overcome the cold start problem of collaborative filtering. In this paper, we study the feasibility of cross-product category usage of user profiles, and suggest a method to improve recommendation performance of cross-product category user profiling. First, we investigate whether user profiles on a product category can be used to recommend products in other product categories. Furthermore, a way of utilizing user profiles selectively is suggested to increase recommendation performance of cross-product category user profiling. The feasibility of cross-product category user profiling and the usefulness of the proposed method are tested with real click stream data of an Internet storefront which sells multiple product categories including books, music CDs, and DVDs. The experiment results show that user profiles on a product category can be used to recommend products in other product categories. Also, the selective usage of user profiles based on correlations between subcategories of two product categories provides better performance than the whole usage of user profiles.

Machine Learning-based model for predicting changes in user evaluation reflecting the period of the product (제품 사용 기간을 반영한 기계학습 기반 사용자 평가 변화 예측 모델)

  • Boo Hyunkyung;Kim Namgyu
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.19 no.1
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    • pp.91-107
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    • 2023
  • With the recent expansion of the commerce ecosystem, a large number of user evaluations have been produced. Accordingly, attempts to create business insights using user evaluation data have been actively made. However, since user evaluation can change after the user experiences the product, it is difficult to say that the analysis based only on reviews immediately after purchase fully reflects the user's evaluation of the product. Moreover, studies conducted so far on user evaluation have overlooked the fact that the length of time a user has used a product can affect the user's product evaluation. Therefore, in this study, we build a model that predicts the direction of change in the user's rating after use from the user's rating and reviews immediately after purchase. In particular, the proposed model reflects the product's period of use in predicting the change direction of the star rating. However, since the posterior information on the duration of product use cannot be used as input in the inference process, we propose a structure that utilizes information about the product's period of use using an auxiliary classifier. As a result of an experiment using 599,889 user evaluation data collected from the shopping platform 'N' company, we confirmed that the proposed model performed better than the existing model in terms of accuracy.

KOMPSAT-2 COMMERCIAL USER SUPPORT TEAM (KOCUST) - ORGANIZATION AND ITS OPERATIONAL CONCEPTS -

  • Kim, Youn-Soo;Jeun, Gab-Ho;Jeun, Jung-Nam;Blet, Didier
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.808-811
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    • 2006
  • The KOMPSAT-2 was developed by KARI and it was successfully launched from Plesetsk, Russia on 28th July 2006. The Korean government decided the commercialization of the KOMPSAT-2 image data and direct reception services worldwide. SPOT Image, based in Toulouse (France) was selected by KARI through an international open bidding as a foreign company for the KOMPSAT-2 image promotion over the entire world except the territory of Republic of Korea including the North Korea, the United States of America, UAE, Saudi Arabia, Kuwait, Qatar, Oman, Yemen, Egypt, Iran, Iraq, Jordan, Lebanon, and Syria. KAI (Korea Aerospace Industry Ltd.) is an engaged Korean company for this area. KARI has responsibility to operate the satellite, data acquisition, archiving for the worldwide commercialization. For the processing and delivery of the KOMPSAT-2 image data to the users of KAI and SPOT Image, KAI has the binding contract with KARI. So KAI has the responsibility for the commercial ground station operation such as user support, data processing, and the data delivery. The KOMPSAT-2 ground station is hosted in KARI, so KARI has developed the concept of KOCUST (KOMPSAT-2 Commercial User Support Team) jointly with KAI to support the data processing and delivery as KOMPSAT-2 developer and satellite operator. The main purpose of the KOCUST is to support the operational activities to provide the data and service quality to satisfy customers. KOCUST will be organized by the members of KARI and KAI together. KARI members will mainly take the role of KOCUST coordination, data processing and user support in a public sector. KAI members are going to take user desk, data validation and delivery et cetera, which are related with users. This paper describes a summarized concepts of KOCUST like organization, dedicated tasks of each part and work flow of daily operation.

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A Study on the attack technique using android UI events (안드로이드 UI 이벤트를 이용한 공격 기법 연구)

  • Yoon, Seok-Eon;Kim, Min-Sung;Lee, Sang-jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.3
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    • pp.603-613
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    • 2015
  • Smart-phone Applications are consists of UI(User Interface). During using applications, UI events such as button click and scroll down are transmitted to Smart-phone system with many changes of UI. In these UI events, various information including user-input data are also involved. While Keylogging, which is a well-known user-input data acquisition technique, is needed a restrictive condition like rooting to obtain the user-input data in android environment, UI events have advantage which can be easily accessible to user-input data on user privileges. Although security solutions based keypad in several applications are applied, we demonstrate that these were exposed to vulnerability of application security and could be obtained user-input data using UI events regardless of presence of any security system. In this paper, we show the security threats related information disclosure using UI events and suggest the alternative countermeasures by showing the replay-attack example based scenarios.