%0 Book Section %1 noKey %A Maarry, KindaEl %A Balke, Wolf-Tilo %A Cho, Hyunsouk %A Hwang, Seung-won %A Baba, Yukino %B Database Systems for Advanced Applications %D 2014 %E Han, Wook-Shin %E Lee, Mong Li %E Muliantara, Agus %E Sanjaya, Ngurah Agus %E Thalheim, Bernhard %E Zhou, Shuigeng %I Springer Berlin Heidelberg %K myown %P 376-387 %R 10.1007/978-3-662-43984-5_29 %T Skill Ontology-Based Model for Quality Assurance in Crowdsourcing %U http://dx.doi.org/10.1007/978-3-662-43984-5_29 %X Crowdsourcing continues to gain more momentum as its potential becomes more recognized. Nevertheless, the associated quality aspect remains a valid concern, which introduces uncertainty in the results obtained from the crowd. We identify the different aspects that dynamically affect the overall quality of a crowdsourcing task. Accordingly, we propose a skill ontology-based model that caters for these aspects, as a management technique to be adopted by crowdsourcing platforms. The model maintains a dynamically evolving ontology of skills, with libraries of standardized and personalized assessments for awarding workers skills. Aligning a worker’s set of skills to that required by a task, boosts the ultimate resulting quality. We visualize the model’s components and workflow, and consider how to guard it against malicious or unqualified workers, whose responses introduce this uncertainty and degrade the overall quality. %@ 978-3-662-43983-8

@incollection{noKey, abstract = {Crowdsourcing continues to gain more momentum as its potential becomes more recognized. Nevertheless, the associated quality aspect remains a valid concern, which introduces uncertainty in the results obtained from the crowd. We identify the different aspects that dynamically affect the overall quality of a crowdsourcing task. Accordingly, we propose a skill ontology-based model that caters for these aspects, as a management technique to be adopted by crowdsourcing platforms. The model maintains a dynamically evolving ontology of skills, with libraries of standardized and personalized assessments for awarding workers skills. Aligning a worker’s set of skills to that required by a task, boosts the ultimate resulting quality. We visualize the model’s components and workflow, and consider how to guard it against malicious or unqualified workers, whose responses introduce this uncertainty and degrade the overall quality.}, added-at = {2015-01-05T15:39:10.000+0100}, author = {Maarry, KindaEl and Balke, Wolf-Tilo and Cho, Hyunsouk and Hwang, Seung-won and Baba, Yukino}, biburl = {https://www.bibsonomy.org/bibtex/2ab4d86aacb6e46394c531ec0b11251c2/balke}, booktitle = {Database Systems for Advanced Applications}, description = {Skill Ontology-Based Model for Quality Assurance in Crowdsourcing - Springer}, doi = {10.1007/978-3-662-43984-5_29}, editor = {Han, Wook-Shin and Lee, Mong Li and Muliantara, Agus and Sanjaya, Ngurah Agus and Thalheim, Bernhard and Zhou, Shuigeng}, interhash = {4c4cbc73c9f0d04a978a6fa26c51b57a}, intrahash = {ab4d86aacb6e46394c531ec0b11251c2}, isbn = {978-3-662-43983-8}, keywords = {myown}, language = {English}, pages = {376-387}, publisher = {Springer Berlin Heidelberg}, series = {Lecture Notes in Computer Science}, timestamp = {2015-01-05T15:39:10.000+0100}, title = {Skill Ontology-Based Model for Quality Assurance in Crowdsourcing}, url = {http://dx.doi.org/10.1007/978-3-662-43984-5_29}, year = 2014 }