Abstract:
Systems and methods for determining a group recommendation of an object, such as a restaurant, movie, or other object, from a plurality of candidate objects based on user comparisons of characteristic traits of the candidate objects are provided. In particular, keywords associated with characteristic traits are identified. The keywords are then presented to members of the group as a series of selection queries. The selection queries require a user to select or rank the keywords based on user preferences. The responses to the selection queries are used to generate a ranking score for each of the plurality of candidate objects and to select one or more of the candidate objects to recommend to the group.
Abstract:
Described is a technique for managing a workflow of human intelligence tasks based on task performance. When a large batch of tasks is performed continuously by a worker, task performance may decline. To lessen these consequences and improve overall task performance, the techniques described herein may adjust the type of tasks provided during a workflow. These adjustments may include providing a workflow interruption in the form of a different type of task or a break activity. These interruptions may switch between conceptual and perceptual activities in order to refresh the user and aid in alleviating the negative consequences of repetitive tasks such as physical and cognitive fatigue.
Abstract:
Implementations provide an improved system for presenting search results based on entity associations of the search items. An example method includes, for each of a plurality of crowdsource workers, initiating display of a first randomly selected cluster set from a plurality of cluster sets to the crowdsource worker. Each cluster set represents a different clustering algorithm applied to a set of search items responsive to a query. The method also includes receiving cluster ratings for the first cluster set from the crowdsource worker and calculating a cluster set score for the first cluster set based on the cluster ratings. This is repeated for remaining cluster sets in the plurality of cluster sets. The method also includes storing a cluster set definition for a highest scoring cluster set, associating the cluster set definition with the query, and using the definition to display search items responsive to the query.