Exact(10)
The recommendation strategy is adjusted over time based on feedback.
A recommendation strategy based on a Markov model is established to tackle this issue.
With this framework the setup evaluation presumes the existence of a common dataset, a common interface and the mechanism to change the recommendation strategy, aiming by this to measure the user's satisfaction according to the used recommendation strategy.
Reinforcement Learning techniques enable the recommendation system to adjust its recommendation strategy over time based on user ratings.
The recommendation system adapts its recommendation strategy over time based on user ratings from previous composition processes.
Hayes et al. (2002) propose an evaluation framework which is based on the idea of system utility by comparing how a recommendation strategy performs against another.
Similar(50)
Task Recommendation strategies recommend tasks to workers according to some affinity criteria [85].
Our system will recommend items based on modified versions of two popular Recommendation strategies– Aggregated Voting and Least Misery.
The method may be useful to improve task recommendation strategies.
These concepts may inspire tasks scheduling and task recommendation strategies in human computation.
So it is necessary to design feasible recommendation strategies to provide users with their expected services.
More suggestions(15)
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