Crowdsourcing Essay Example | Topics and Well Written Essays - 750 words

Crowdsourcing - Essay ExampleMost studies done on crowdsourcing have focused much on the tonicity of results and throughput with in truth or no attention on efficiency or the tradeoff therein. This is because the number of tasks to be performed is usually very small. Additionally, the tasks performed by users atomic number 18 also small, and as a result, the techniques apply to guarantee result quality and scale the tasks that arise, does not tackle the aspect of efficiency. This paper aims at evaluating animate result-improvement mechanism, and proposes a novel technique that is independent of task complexities and size, but ensures efficiency and a tradeoff in the midst of quality of results and efficiency. Keywords Efficiency Throughput Result Quality Crowdsourcing Data INTRODUCTION Crowdsourcing is very popular and has become very important for info collection-labeled data- that are dependent on valet de chambre input to ensure quality of data as demonstrated by reCAPTCH A, Amazon Mechanical Turk, ESP game, and Netflix among others. Crowdsourcing is the distribution of small chunks of large, complicated tasks to a large community of users over the internet who offers small contributions towards solving or offering a antecedent (Brabham 2008). In addition to data labeling, crowdsourcing has been utilized in double keying individual words, image labeling, word disambiguation and order of word pairs that depict relatedness (Sautter & Bohm 2011). There are a number of challenges that arise from crowdsourcing including lack of guarantees for correctness with regards to human inputs. This can be as a result of accidental mistakes resulting from misjudgment or sloppiness. Sometimes, users may cheat to annex their chances of receiving a reward by cheating to reduce their effort. These challenges require development of crowdsourcing techniques that can ensure data quality, efficiency, counter errors, work with very large data sets, and yield high throughp ut. Previous studies and crowdsourcing mechanisms such as r-Redundancy, have focused more on working with large tasks, countering errors, yielding high throughput and ensuring data quality (Eckert et al. 2010). This study, however, proposes novel techniques that are independent of task complexities and size but ensure efficiency and enables tradeoff amidst quality of results and efficiency. THE NEED FOR EFFICIENT CROWDSOURCING TECHNIQUES FOR COMPLEX TASKS Crowdsourcing mechanisms such as r-Redundancy, have focused more on working with large tasks, countering errors, yielding high throughput and ensuring data quality. They have assumed that most users offer meaningful and correct inputs. These mechanisms have ensured data quality, even in the presence of dishonesty, cheating and inability but do not discourage such a behavior (Wauthier & Jordan 2011). Therefore, a mechanism that probes users, is required, one that would not single ensure quality and high throughput, but ensure effi ciency, as well. OVERVIEW OF EFFICIENT CROWDSOURCING TECHNIQUES FOR COMPLEX TASKS There are crowdsourcing techniques that combine error countering, data quality enforcement, and large tasks handling. v-Voting is one such mechanism that mostly focuses on countering errors (Alonso et al. 2008). It reduces the required number of inputs unlike r-Redundancy by obtaining inputs from different users and combining them to the final result. There is also choose Boosting, which is a mechanism that builds on v-Voting to increases throughput