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Selecting Workers Wisely for Crowdsourcing When Copiers and Domain Experts Co-exist

Xiu Fang, Suxin Si, Guohao Sun, Quan Z. Sheng, Wenjun Wu, Kang Wang, Hang Lv
2022 Future Internet  
We designed a crowdsourcing system called SWWC composed of a task assignment stage and a truth discovery stage.  ...  Based on this measurement and prior task domain knowledge, we calculated fine-grained worker credibility on each given task.  ...  Acknowledgments: We are grateful for the server provided by Donghua University to assist us in running the experiment and obtaining the experimental data and results in a short time.  ... 
doi:10.3390/fi14020037 fatcat:5gtjn3z25fhflbnf4qm2zgp5bu

Geotagging: Systematic Anatomization and Conceptual Model for POI Verification

2020 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Therefore, a framework is required to expedite the tagging and authentication process of the tagged data in an efficient manner to exploit the power of POI data.  ...  Hence, it's a need of hour to enrich the unique Indian GIS portal "Bhuvan" with Point of Interest (POI) data where one can find all necessary information.  ...  Multi-source information trustworthiness analysis framework and fine-grained truth discovery model were proposed to find the truth in crowdsourced generated data [26, 27] .  ... 
doi:10.35940/ijitee.k7820.0991120 fatcat:twxah67m2vdldaweyqtrgvnh4a

FaitCrowd

Fenglong Ma, Jiawei Han, Yaliang Li, Qi Li, Minghui Qiu, Jing Gao, Shi Zhi, Lu Su, Bo Zhao, Heng Ji
2015 Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15  
To capture various expertise levels on different topics, we propose FaitCrowd, a fine grained truth discovery model for the task of aggregating conflicting data collected from multiple users/sources.  ...  In crowdsourced data aggregation task, there exist conflicts in the answers provided by large numbers of sources on the same set of questions.  ...  Figure 1 shows the proposed fine grained truth discovery model for crowdsourced data aggregation.  ... 
doi:10.1145/2783258.2783314 dblp:conf/kdd/MaLLQGZSZJH15 fatcat:vm2d6l4am5h7xedinlgendhhzm

A Survey on Truth Discovery [article]

Yaliang Li, Jing Gao, Chuishi Meng, Qi Li, Lu Su, Bo Zhao, Wei Fan, Jiawei Han
2015 arXiv   pre-print
We hope that this survey will promote a better understanding of the current progress on truth discovery, and offer some guidelines on how to apply these approaches in application domains.  ...  Thanks to information explosion, data for the objects of interest can be collected from increasingly more sources.  ...  Recently, a series of approaches [5, 26, 60, [66] [67] [68] [69] have adopted truth discovery to improve the aggregation quality of such noisy sensing data. • Crowdsourcing aggregation.  ... 
arXiv:1505.02463v2 fatcat:sqvfxldfqjbtlexi5gqaldtgqq

Truth Inference with a Deep Clustering-based Aggregation Model

Liang Yin, Yunfei Liu, Weinan Zhang, Yong Yu
2020 IEEE Access  
Therefore, the proposed model is a novel approach for truth inference with object features.  ...  DCAM introduces clustering for object features to form fine-grained clusters, where objects in the same cluster are supposed to have similar labels.  ...  INTRODUCTION Truth inference aims at inferring true labels or objective opinions from different sources, which is also known as truth discovery or label aggregation for crowdsourcing tasks [25] , [49  ... 
doi:10.1109/access.2020.2964484 fatcat:fismxfy6avhsllrufd4xddvofe

Can The Crowd Identify Misinformation Objectively? The Effects of Judgment Scale and Assessor's Background [article]

Kevin Roitero, Michael Soprano, Shaoyang Fan, Damiano Spina, Stefano Mizzaro, Gianluca Demartini
2020 arXiv   pre-print
In this paper, we follow a different approach and rely on (non-expert) crowd workers.  ...  This of course leads to the following research question: Can crowdsourcing be reliably used to assess the truthfulness of information and to create large-scale labeled collections for information credibility  ...  We can observe a higher failure and lower completion rate for S 100 . This may show a slight lack of comfort for workers in using the most fine-grained scale.  ... 
arXiv:2005.06915v1 fatcat:u3utoxzp5ncx3f5dvrvk2zsfy4

A Survey on Security, Privacy, and Trust in Mobile Crowdsourcing

Wei Feng, Zheng Yan, Hengrun Zhang, Kai Zeng, Yu Xiao, Y. Thomas Hou
2018 IEEE Internet of Things Journal  
., smart phones and wearable devices), Mobile Crowdsourcing (MCS) has emerged as an effective method for data collection and processing.  ...  This paper provides a survey of these challenges and discusses potential solutions.  ...  Ye et al. proposed a context-aware fine-grained access control scheme for the data stored in mobile devices [91] .  ... 
doi:10.1109/jiot.2017.2765699 fatcat:eapkruonuzh6hhzppoumnonlhq

Teddy: A System for Interactive Review Analysis [article]

Xiong Zhang and Jonathan Engel and Sara Evensen and Yuliang Li and Çağatay Demiralp and Wang-Chiew Tan
2020 arXiv   pre-print
Results suggest data scientists need interactive systems for many review analysis tasks.  ...  Today, data scientists analyze reviews by developing rules and models to extract, aggregate, and understand information embedded in the review text.  ...  ACKNOWLEDGMENTS We thank our study participants for their time and insights. We also thank Eser Kandogan for his feedback on an earlier draft of this paper.  ... 
arXiv:2001.05171v1 fatcat:2l5fnifhlneqjkbmhpoivwrjqm

Harnessing the Power of the General Public for Crowdsourced Business Intelligence: A Survey

Bin Guo, Yan Liu, Yi Ouyang, Vincent W. Zheng, Daqing Zhang, Zhiwen Yu
2019 IEEE Access  
This paper first characterizes the concept model and unique features and presents a generic framework for CrowdBI.  ...  Crowdsourced business intelligence (CrowdBI), which leverages the crowdsourced usergenerated data to extract useful knowledge about business and create marketing intelligence to excel in the business environment  ...  FINE-GRAINED DATA COLLECTION There are numerous issues regarding data collection from different data sources. 1) PERVASIVE SENSING For fine-grained human offline shopping behavior sensing, there are  ... 
doi:10.1109/access.2019.2901027 fatcat:a5vz6vl7urckpdsreplkvjalea

ICDE conference 2015 detailed author index

2015 2015 IEEE 31st International Conference on Data Engineering  
Schema-Flexible RDBMS [Search] A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Waguih, Dalia Attia 1440 AllegatorTrack: Combining and Reporting Results of Truth Discovery from Multi-Source Data Wang  ...  Detection Li, Xiaoli 831 Network Motif Discovery: A GPU Approach 1452 CDR-To-MoVis: Developing a Mobility Visualization System from CDR Data Li, Xin 1436 MARS: A Multi-Aspect Recommender  ... 
doi:10.1109/icde.2015.7113260 fatcat:ep7pomkm55f45j33tkpoc5asim

Quality of Information in Mobile Crowdsensing

Francesco Restuccia, Nirnay Ghosh, Shameek Bhattacharjee, Sajal K. Das, Tommaso Melodia
2017 ACM transactions on sensor networks  
For a survey on mobile crowdsensing applications, we refer the reader to [92] .  ...  In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic.  ...  ACKNOWLEDGEMENT We would like to thank the anonymous reviewers for their valuable comments, which helped us improve the quality of the paper.  ... 
doi:10.1145/3139256 fatcat:hgq6lcwmofhy3gpq4auqxuhggu

Smartphone-based crowdsourcing for network monitoring: Opportunities, challenges, and a case study

Adriano Faggiani, Enrico Gregori, Luciano Lenzini, Valerio Luconi, Alessio Vecchio
2014 IEEE Communications Magazine  
Our experience in building a smartphonebased crowdsourcing system, Portolan, is also included to provide a practical background to the discussion and to demonstrate the possible benefits.  ...  This paper discusses the most significant opportunities offered by this approach, and the major challenges that have to be faced.  ...  We believe that fine-grained information like this can be extremely valuable for telecom operators, as it would allow them a fine tuning of wireless access infrastructure.  ... 
doi:10.1109/mcom.2014.6710071 fatcat:pscn5gckfjgxllh4t5vtz3uvte

Fine-grained object recognition in underwater visual data

C. Spampinato, S. Palazzo, P. H. Joalland, S. Paris, H. Glotin, K. Blanc, D. Lingrand, F. Precioso
2015 Multimedia tools and applications  
Together with the fine-grained visual dataset release, we also present two approaches for fish species classification in, respectively, still images and videos.  ...  In this paper we investigate the fine-grained object categorization problem of determining fish species in low-quality visual data (images and videos) recorded in real-life settings.  ...  In order to provide a baseline for our fish species classification methods we tested 1) the VLfeat BoW [37] classification method (generally used as baseline for fine-grained recognition tasks [6] )  ... 
doi:10.1007/s11042-015-2601-x fatcat:hxf2xw6thzagfnrlti3qibfufq

Can the Crowd Judge Truthfulness? A Longitudinal Study on Recent Misinformation about COVID-19 [article]

Kevin Roitero and Michael Soprano and Beatrice Portelli and Massimiliano De Luise and Damiano Spina and Vincenzo Della Mea and Giuseppe Serra and Stefano Mizzaro and Gianluca Demartini
2021 arXiv   pre-print
Recently, the misinformation problem has been addressed with a crowdsourcing-based approach: to assess the truthfulness of a statement, instead of relying on a few experts, a crowd of non-expert is exploited  ...  In our experiments, crowd workers are asked to assess the truthfulness of statements, and to provide evidence for the assessments.  ...  Acknowledgements This work is partially supported by a Facebook Research award, by the Australian Research Council (DP190102141 and DE200100064), by a MISTI -MIT International Science and Technology Initiatives  ... 
arXiv:2107.11755v1 fatcat:pxyasrohpvdevcnbfx42utklfy

Crowdclustering

Ryan Gomes, Peter Welinder, Andreas Krause, Pietro Perona
2011 Neural Information Processing Systems  
Amongst the challenges: (a) each worker has only a partial view of the data, (b) different workers may have different clustering criteria and may produce different numbers of categories, (c) the underlying  ...  Is it possible to crowdsource categorization?  ...  A similar approach was proposed by Welinder et al. [3] for the analysis of classification labels obtained from crowdsourcing services.  ... 
dblp:conf/nips/GomesWKP11 fatcat:tkicmfpnmvdkjeaqitjrcofs7i
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