Abstract: A system combines inputs from human processing and machine processing, and employs machine learning to improve processing of individual tasks based on comparison of human processing results. Once performance of a particular task by machine processing reaches a threshold, the level of human processing used on that task is reduced.

Abstract: Methods, systems, and media for identifying errors in predictive models using annotators are provided. In some embodiments, a method for evaluating predictive models in classification systems is provided, the method comprising: causing an input region to be presented to a user, where the input region receives an instance from the user that corresponds to a predictive model; retrieving a classification conducted by the predictive model for the received instance and a confidence value associated with the classification; determining whether the received instance has been incorrectly classified by the predictive model; determining a reward associated with the incorrect classification made by the predictive model in response to determining that the received instance has been incorrectly classified by the predictive model, where the reward is based on the confidence value associated with the classification of the received instance; and providing the reward to the user.

Abstract: A system combines inputs from human processing and machine processing, and employs machine learning to improve processing of individual tasks based on comparison of human processing results. Once performance of a particular task by machine processing reaches a threshold, the level of human processing used on that task is reduced.

Abstract: A system combines inputs from human processing and machine processing, and employs machine learning to improve processing of individual tasks based on comparison of human processing results. Once performance of a particular task by machine processing reaches a threshold, the level of human processing used on that task is reduced.

Abstract: A non-transitory computer-readable medium, method and system for providing results associated with a ranking of a plurality of items of a particular item type can be provided. For example, for each respective item of a plurality of items having an associated cost, it is possible to (i) determining an item utility value for the respective item of the items based on aggregate data associated with a plurality of users without requiring utilization of information particular to each of the users, and (ii) determine a surplus value for the respective item as the item utility value less a cost utility value associated with the cost of the respective item. Further, it is possible to provide the results, based on the respective surplus values, to a particular user of the users.

Abstract: Methods, systems, and media for identifying errors in predictive models using annotators are provided. In some embodiments, a method for evaluating predictive models in classification systems is provided, the method comprising: causing an input region to be presented to a user, where the input region receives an instance from the user that corresponds to a predictive model; retrieving a classification conducted by the predictive model for the received instance and a confidence value associated with the classification; determining whether the received instance has been incorrectly classified by the predictive model; determining a reward associated with the incorrect classification made by the predictive model in response to determining that the received instance has been incorrectly classified by the predictive model, where the reward is based on the confidence value associated with the classification of the received instance; and providing the reward to the user.

Abstract: An exemplary system, method and computer-accessible medium can be provided that can be used, for example, for evaluating a test question(s) for a test(s), which can include receiving information related to a content(s), mapping the content(s) to a skill(s), and evaluating the content(s) as the test question(s) so as to test an ability of user(s) at the skill(s).

Abstract: An exemplary system, method and computer-accessible medium can be provided, which can include, for example, receiving digital data related to a suspicious trade(s), determining a first entity(s) associated with the suspicious trade(s) based on the digital data, and determining a relationship between the first entity(s) and a second entity based(s) on a proximity between the first entity(s) and the second entity(s). The proximity used to determine the relationship can be a logical proximity. The logical proximity can be determined based on a communication(s) between the first entity(s) and the second entity(s).

Abstract: Exemplary systems, methods and computer-accessible mediums can be provided which can receive information related to a consumer(s), and determine the search behavior of the consumer(s) based on the information and using a consumer search model that is based on heterogeneous preferences and a search cost model of a second consumer(s).

Abstract: A non-transitory computer-readable medium, method and system for providing results associated with a ranking of a plurality of items of a particular item type can be provided. For example, for each respective item of a plurality of items having an associated cost, it is possible to (i) determining an item utility value for the respective item of the items based on aggregate data associated with a plurality of users without requiring utilization of information particular to each of the users, and (ii) determine a surplus value for the respective item as the item utility value less a cost utility value associated with the cost of the respective item. Further, it is possible to provide the results, based on the respective surplus values, to a particular user of the users.

Abstract: A system combines inputs from human processing and machine processing, and employs machine learning to improve processing of individual tasks based on comparison of human processing results. Once performance of a particular task by machine processing reaches a threshold, the level of human processing used on that task is reduced.

Abstract: A system, method, software arrangement and computer-accessible medium can be provided for incorporating quantitative and qualitative information into an economic model is provided. An exemplary method for analyzing qualitative information associated with a characteristic of at least one entity based on associated quantitative information, includes, obtaining first information which contains at least in part a qualitative information relating to at least one of the at least one entity; determining second information associated with at least one attribute of the characteristic obtained from the first information; obtaining third information which contains at least in part quantitative information associated with at least one of at least one entity; and establishing fourth information as a function of the second information and the third information to determine which of at least one attribute affects the characteristic.

Abstract: A system, method, software arrangement and computer-accessible medium can be provided for incorporating quantitative and qualitative information into an economic model is provided. An exemplary method for analyzing qualitative information associated with a characteristic of at least one entity based on associated quantitative information, includes, obtaining first information which contains at least in part a qualitative information relating to at least one of the at least one entity; determining second information associated with at least one attribute of the characteristic obtained from the first information; obtaining third information which contains at least in part quantitative information associated with at least one of at least one entity; and establishing fourth information as a function of the second information and the third information to determine which of at least one attribute affects the characteristic.