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@article{145841,
        author = {D.Ajay kumar and M.PADMAVATHAMMA},
        title = {The importance of worker Reputation information of in Microtask-Based crowd work Systems },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {4},
        number = {11},
        pages = {968-971},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=145841},
        abstract = {This paper  presents we first formalize the optimal task assignment problem when workers’ reputation estimates are available, as the maximization of a monotone (submodular) function subject to Matroid constraints. Then, being the optimal problem NP-hard, we propose a simple but efficient greedy heuristic task allocation algorithm. We also propose a simple “maximum a-posteriori” decision rule and a decision algorithm based on message passing. Finally, we test and compare different solutions, showing that system performance can greatly benefit from information about workers’ reputation. In this our main findings are that: i) even largely inaccurate estimates of workers’ reputation can be effectively exploited in the task assignment to greatly improve system performance; ii) the performance of the maximum a-posteriori decision rule quickly degrades as worker reputation estimates become inaccurate; iii) when workers’ reputation estimates are significantly inaccurate, the best performance can be obtained by combining our proposed task assignment algorithm with the message-passing decision algorithm},
        keywords = {a-priori, micro task, a-posteriori, message passing},
        month = {},
        }