• Korea Information Processing Society Review
• /
• v.29 no.1
• /
• pp.51-60
• /
• 2022

• Spatial Information Research
• /
• v.23 no.1
• /
• pp.49-57
• /
• 2015

Due to high density of population and progress of high building construction technologies, the number of high buildings has been increasing. Several information services have been provided to figure out complex indoor structures of building such as indoor navigations and indoor map services. The most fundamental information for these services are indoor network information. Indoor network in building provides topological connectivity between spaces unlike geometric information of buildings. In order to make indoor network information, we have to edit network manually or derive network properties based on the geometric data of buildings. This process is not easy for complex buildings. In this paper, we suggest a method to generate indoor network automatically based on crowdsourcing. From the collected individual trajectories, we derive indoor network information with crowdsourcing. We validate our method with a sample set of trajectory data and the result shows that our method is practical if the indoor positioning technology is reasonably accurate.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.4
• /
• pp.61-72
• /
• 2018

The purpose of this study is to analyze the impact of quality and satisfaction of mobile telecommunication service on the quality data sharing for mobile telecommunication service. Based on the theory of reasoned action(TRA), we proposed a research model that (1) service qualities significantly influence the service satisfaction and the attitude towards information sharing, (2) the attitude towards information sharing mediates between service satisfaction and the intention of information sharing, and (3) the intention of information sharing is affected by the service satisfaction and the attitude towards information sharing. Empirical analysis of mobile service users showed that the data quality of mobile communication services had a greater impact on satisfaction than voice quality. The service satisfaction had a positive effect on attitude towards information sharing and the intention of information sharing. Also, the attitude towards information sharing had a positive impact on the intention of information sharing. Based on this empirical study, we proposed a crowdsourcing as an alternative when quality data of mobile telecommunication service should be collected to improve telecommunication policy because by using collective intelligence of the crowdsourcing the government can gather more accurate and diverse data on mobile telecommunication service.

• Journal of Information Processing Systems
• /
• v.14 no.1
• /
• pp.129-139
• /
• 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.

• Management & Information Systems Review
• /
• v.36 no.1
• /
• pp.251-271
• /
• 2017

This research examined a study on the effect of the self-determination and motivation in the crowdsourcing on the continuous participation intention. This study has classified the three elements of the self-determination which is not forced by outer pressure has intended to analyze practically the effect on the motivation of the customers participating in the crowdsourcing into the intrinsic motivation phase and extrinsic motivation phase. The autonomy, competence and relatedness could be verified with the intrinsic motivation phase of the participants who affect positively the enjoyment and accomplishment. In the effect autonomy, competence and relatedness on the monetary compensation and recognition by others of the extrinsic motivation phase, the hypothesis that the effect autonomy, competence and relatedness of the on the monetary compensation would be negative was overruled, which must have been because while the participation in the crowdsourcing is proposing voluntarily one's own ideas, the concept that the monetary compensation makes the participants participate in order to perceive others not in the voluntary proposals but in the competitive relationships and win them worked and thus the autonomy was perceived negatively. Also, the reason why the relationship between the monetary compensation and the autonomy, competence and relatedness was not supported can be said to be because the crowding-out effect which decreases the intrinsic motivation affected the external compensation and the motivation.

• Journal of Computing Science and Engineering
• /
• v.9 no.4
• /
• pp.190-203
• /
• 2015

Free and open source software (FOSS) has created a large pool of source codes that can be easily copied to create new applications. However, a copy should preserve copyright notice and license of the original file unless the license explicitly permits such a change. Through software evolution, it is challenging to keep original licenses or choose proper licenses. As a result, there are many potential license violations. Despite the fact that violations can have high impact on protecting copyright, identification of violations is highly complex. It relies on manual inspections by experts. However, such inspection cannot be scaled up with open source software released daily worldwide. To make this process scalable, we propose the following two methods: use machine-based algorithms to narrow down the potential violations; and guide non-experts to manually inspect violations. Using the first method, we found 219 projects (76.6%) with potential violations. Using the second method, we show that the accuracy of crowds is comparable to that of experts. Our techniques might help developers identify potential violations, understand the causes, and resolve these violations.

• Journal of Information Processing Systems
• /
• v.14 no.3
• /
• pp.621-630
• /
• 2018

Selection of a suitable task from the extensively available large set of tasks is an intricate job for the developers in crowdsourcing software development (CSD). Besides, it is also a tiring and a time-consuming job for the platform to evaluate thousands of tasks submitted by developers. Previous studies stated that managerial and technical aspects have prime importance in bringing success for software development projects, however, these two aspects can be more effective and conducive if combined with human aspects. The main purpose of this paper is to present a conceptual framework for task assignment model for future research on the basis of personality types, that will provide a basic structure for CSD workers to find suitable tasks and also a platform to assign the task directly. This will also match their personality and task. Because personality is an internal force which whittles the behavior of developers. Consequently, this research presented a Task Assignment Model (TAM) from a developers point of view, moreover, it will also provide an opportunity to the platform to assign a task to CSD workers according to their personality types directly.

• Informatization Policy
• /
• v.23 no.2
• /
• pp.54-72
• /
• 2016

This article analyzes the latest cases of Digital Social Innovation such as crowdsourcing and online petitions for public trouble-shooting in oder to demonstrate that public engagement of the citizens on decision making can enhance the quality of democracy. Digital Social Innovation contributes to citizen's participation on decision making and policy implementation with taking advantage of digital technologies of crowdsourcing and online petitions. Active civic engagement for decision making literally helps to improve and democratize government policy. These series of processes not only improve quality and efficiency of policy governance by building up transparency and effectiveness of policy itself but also enhance the throughput legitimacy. With this article, I quote and analyze various practices of Digital Social Innovation which we had substantiated to demonstrate the effectiveness of civic engagement for decision making to improve and enhance democracy. The hypothesis that the Digital Social Innovation attempted in various ways is a principal factor of democratization could be verified. Moreover, the practices of Digital Social Innovation helps the civic participation in policy making in modern society. Finally, this article suggests an implication of Digital Social Innovation as part of efforts to ensure the involvement of throughput legitimacy for the development of democracy.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_1
• /
• pp.577-587
• /
• 2023

The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.

• Journal of Cadastre & Land InformatiX
• /
• v.46 no.1
• /
• pp.117-131
• /
• 2016

The development of LBS(location-based services) due to the widespread mobile environment highlights the importance of POI(point of interest) information. The accurate and up-to-date POI has to be ensured to reflect the information of rapidly changing places. For the efficient construction of POI, here we propose the novel construction system for t he place information. This system is based on crowd-sourcing in which a great number of users participate. In addition, we utilize the graph data model to build the new concept of the place information covering the wide areas extending from the specific point. Moreover, the implementation of the new system applying the graph data model and crowd-sourcing is realized in this paper. That is, this study suggests the whole new concept of the place information and shows the clustering and the renewal of the place information through crowd-sourcing.