• Journal of Information Science Theory and Practice
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• 제5권2호
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• pp.6-16
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• 2017

Populating information-rich online environments through crowdsourcing is increasingly becoming popular. One approach to motivate participation is via games. That is, a crowdsourcing game offers entertainment while generating useful outputs as byproducts of gameplay. A gap in current research is that actual usage patterns of crowdsourcing games have not been investigated thoroughly. We thus compare content creation patterns in a game for crowdsourcing mobile content against a non-game version. Our analysis of 3,323 contributions in both apps reveal 10 categories including those that conform to the traditional notion of mobile content created to describe locations of interest, and those that are social in nature. We contend that both types of content are potentially useful as they meet different needs. Further, the distribution of categories varied across the apps suggests that games shape behavior differently from non-game-based approaches to crowdsourcing.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제8권1호
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• pp.1-8
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• 2019

본 논문에서는 모바일 크라우드소싱 환경에서 게임이론의 인센티브 매커니즘 기법과 중복 연합 형성 게임(Overlapping Coalition Formation Game)을 적용하여 시스템의 진실성을 보장하고 모바일 노드의 이득을 극대화하는 효율적인 기법을 제안한다. 제안된 매커니즘 기법은 노드가 자신의 정보를 솔직하게 드러냈을 때 가장 높은 보상을 지급함으로써 노드가 진실된 정보를 보고하도록 한다. 또한 중복 연합 형성 게임을 적용함으로써 노드들은 자신 주변의 가장 높은 보상을 지급하는 연합을 선택하고 자신의 자원이 허락하는 한 다수의 연합에 참가하여 업무를 수행함으로써 효율성을 높일 수 있었다. 컴퓨터 시뮬레이션을 통해 기존에 제안된 다른 기법에 비해 제안된 기법은 모바일 노드들이 높은 보상을 얻기 위해 자신의 정보를 솔직하게 드러냈고 자신의 성능과 남은 자원에 따라 더 높은 보상을 받을 수 있음을 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권8호
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• pp.2827-2848
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• 2021

Mobile Crowdsourcing (MCS) has become an emerging paradigm evolved from crowdsourcing by employing advanced features of mobile devices such as smartphones to perform more complicated, especially spatial tasks. One of the key procedures in MCS is to collect answers from mobile users (workers), which may face several security issues. First, authentication is required to ensure that answers are from authorized workers. In addition, MCS tasks are usually location-dependent, so the collected answers could disclose workers' location privacy, which may discourage workers to participate in the tasks. Finally, the overhead occurred by authentication and privacy protection should be minimized since mobile devices are resource-constrained. Considering all the above concerns, in this paper, we propose a lightweight and privacy-preserving answer collection scheme for MCS. In the proposed scheme, we achieve anonymous authentication based on traceable ring signature, which provides authentication, anonymity, as well as traceability by enabling malicious workers tracing. In order to balance user location privacy and data availability, we propose a new concept named current location privacy, which means the location of the worker cannot be disclosed to anyone until a specified time. Since the leakage of current location will seriously threaten workers' personal safety, causing such as absence or presence disclosure attacks, it is necessary to pay attention to the current location privacy of workers in MCS. We encrypt the collected answers based on timed-release encryption, ensuring the secure transmission and high availability of data, as well as preserving the current location privacy of workers. Finally, we analyze the security and performance of the proposed scheme. The experimental results show that the computation costs of a worker depend on the number of ring signature members, which indicates the flexibility for a worker to choose an appropriate size of the group under considerations of privacy and efficiency.

• 전기전자학회논문지
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• 제22권1호
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• pp.29-37
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• 2018

광범위하게 보급된 스마트폰의 다양한 센서들과 통신/사용자 인터페이스 그리고 연산능력을 활용하여 교통정보를 수집하는 모바일 크라우드소싱 시스템에 관한 관심이 최근 증가하고 있다. 본 논문에서는 특정 도로구간을 통과하는 스마트폰 GPS 수신기와 다양한 센서들이 생성한 데이터를 크라우드소싱하고, 대규모 정보처리를 통해 도로구간의 프로파일 정보를 생성하여 이를 해당 도로구간에 진입하는 차량에게 전달하여 운전의 편의성을 향상하는 모바일 크라우드소싱 기반 운전자 지원 시스템(MC-DAS)을 제시한다. MC-DAS 플랫폼을 기반으로 과속방지턱과 도로 곡률을 고려하여 속력조언을 제공하는 내비게이션 시스템을 설계/개발하고, 도로주행 실험을 통해 속력조언 내비게이션 시스템의 동작을 검증하였다. 제안하는 MC-DAS 플랫폼은 향후 스마트폰과 결합된 다양한 서비스를 제공하기 위한 플랫폼으로 활용될 수 있을 것으로 기대한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.4766-4786
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• 2016

Looking for missing companions who are out of touch in public places might suffer a long and painful process. With the help of mobile crowdsourcing, the missing person's location may be reported in a short time. In this paper, we propose MissingFound, an assistant system that applies mobile crowdsourcing for finding missing companions. Discovering valuable users who have chances to see the missing person is the most important task of MissingFound but also a big challenge with the requirements of saving battery and protecting users' location privacy. A customized metric is designed to measure the probability of seeing, according to users' movement traces represented by WiFi RSSI fingerprints. Since WiFi RSSI fingerprints provide no knowledge of users' physical locations, the computation of probability is too complex for practical use. By parallelizing the original sequential algorithms under MapReduce framework, the selecting process can be accomplished within a few minutes for 10 thousand users with records of several days. Experimental evaluation with 23 volunteers shows that MissingFound can select out the potential witnesses in reality and achieves a high accuracy (76.75% on average). We believe that MissingFound can help not only find missing companions, but other public services (e.g., controlling communicable diseases).

• 한국인터넷방송통신학회논문지
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• 제18권4호
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• pp.61-72
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• 2018

본 연구의 목적은 이동통신서비스 환경에서 서비스 사용자가 인지한 품질과 서비스 사용을 통한 만족 등의 요소가 사업자와의 상호 작용을 통해 획득한 정보 공유태도, 정보공유의도에 미치는 영향을 설명하는데 있다. 이는 현재 정부의 통신서비스 품질 정책 수립을 위해 베타터스터 및 측정 장비를 활용하여 측정하고 그 결과를 분석하는 방식에서, 국민이 품질측정시스템에 직접 접속하여 측정한 품질측정 정보에 대한 만족, 정보 공유의사확인을 통해 어떤 소비자가 공유의사가 높은지, 통계적 타당성 확보를 통한 정책적 아이디어를 제공하고자 하였다. 이동통신서비스 이용자를 대상으로 실증분석결과, 이동통신서비스의 데이터 품질은 음성품질보다 만족에 큰 영향을 끼쳤으며, 품질요소와 만족, 정보공유태도와 의도에 긍정적인 영향을 끼침을 확인할 수 있었다. 이러한 실증적 연구결과를 바탕으로 국민의 품질측정데이터 공유의도 확인을 통해 크라우드 소싱을 활용한 정책사례로 추진 가능한 실무적 시사점을 제시하였다.

• 대한건축학회논문집:계획계
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• 제35권8호
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• pp.47-56
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• 2019

The purpose of this study is to explore the possibility of using crowdsourcing as a means to expand the participation of citizens in the process of smart urban regeneration New Deal policy. Using mobile devices, they built a crowdsourcing prototype system that enables residents to provide location-based ideas and opinions about the urban regeneration New Deal policy and share and manage the collected data. The system was applied to the actual urban regeneration New Deal project site to draw implications. The main research results are as follows. First, crowdsourcing is a means of strengthening expertise by utilizing collective intelligence dispersed among local residents. Through the online platform developed in this study, various ideas and opinions of the community can be collected. Second, the procedural legitimacy and transparency of the rehabilitation project can be secured by expanding the participation opportunities of the residents. Third, the efficiency of project promotion can be improved through participation of residents using online platform.

• Architectural research
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• 제20권4호
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• pp.109-120
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• 2018

In the context of ever-faster urbanization, cities are becoming increasingly complex, and data collection to understand such complex relationships is becoming a very important factor. This paper focuses on the lighter weight of the method of collecting urban data, and studied how to use such complementary data collection using crowdsourcing. Especially, the method of converting mobile acceleration sensor information to urban trip information by combining with locational information was experimented. Using the parameters for transportation type classification obtained from the research, information was obtained and verified in Singapore and Zurich. The result of this study is thought to be a good example of how to combine raw data into meaningful behavior information.

• Journal of Information Processing Systems
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• 제14권1호
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• pp.129-139
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• 2018

The crowdsourcing software development (CSD) is growing rapidly in the open call format in a competitive environment. In CSD, tasks are posted on a web-based CSD platform for CSD workers to compete for the task and win rewards. Task searching and assigning are very important aspects of the CSD environment because tasks posted on different platforms are in hundreds. To search and evaluate a thousand submissions on the platform are very difficult and time-consuming process for both the developer and platform. However, there are many other problems that are affecting CSD quality and reliability of CSD workers to assign the task which include the required knowledge, large participation, time complexity and incentive motivations. In order to attract the right person for the right task, the execution of action plans will help the CSD platform as well the CSD worker for the best matching with their tasks. This study formalized the task assignment method by utilizing different situations in a CSD competition-based environment in artificial intelligence (AI) planning. The results from this study suggested that assigning the task has many challenges whenever there are undefined conditions, especially in a competitive environment. Our main focus is to evaluate the AI automated planning to provide the best possible solution to matching the CSD worker with their personality type.

• 한국콘텐츠학회논문지
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• 제22권4호
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• pp.83-93
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• 2022

운전자가 모바일기기를 사용하여 직접 교통 정보를 제공하는 크라우드 소싱을 활용하여 교통 문제를 해결하려는 연구들이 진행 중이다. 크라우드 소싱을 통해 수집된 데이터를 교통 이벤트 검출에 사용한다면 관련된 데이터를 수집하는 작업이 줄어들어 시간 비용이 낮아지고 정확도는 높아지는 장점이 있다. 본 논문에서는 크라우드 소싱을 활용하여 교통과 관련된 데이터를 수집하고, 이를 통해 교통에 영향을 미치는 이벤트를 검출하는 기법을 제안한다. 제안하는 기법은 대용량 데이터 처리를 위해 기계 학습 알고리즘을 사용하여 수집된 데이터의 이벤트 유형을 판별한다. 또한, 이벤트가 발생된 위치를 추출하기 위하여 수집된 데이터에서 위치를 나타내는 키워드를 추출하고 키워드의 행정구역을 반환한다. 이를 통해 기존 제공되는 위치 정보에서 광범위하게 정의된 위치나 잘못된 위치 정보를 해결할 수 있다. 제안하는 기법의 타당성을 입증하기 위해 다양한 성능 평가를 수행한다.