Games with a purpose (GWAPs) are an example of an emerging class of games that uses gamification and human computation power to collect data from the interaction with human users.
We remove the test data from the interaction score matrix G, and predict whether a test gene pair is alleviating using the probability that u and v occur together in a linear pathway, i.e. P u, v → + P u, v ←.
"Further, with its owners' permission, aibo can collect data from these interactions, then connect to the cloud and access the knowledge accumulated from interactions between different owners and their aibo to become even more clever".
In terms of complex networks, the focus of studies is typically on data retrieved from the interactions of various CAS agents/components.
Each touchpoint becomes an opportunity to build a better understanding of customers; data from these interactions can improve the company's marketing stack and explode lead generation, not to mention conversions.
Interaction data are data from the users' interaction with a system such as observational data, system logs, and data from think-aloud protocols.
Some of the missed interactions may be false positives, and thus at this front our analysis would serve to purge such data from the genetic interaction maps.
Through analysis of data from the team interaction, participant perspectives, and ethnographic context, it is demonstrated that the NS takes on an expert identity, while the NNS takes on a novice identity as the NS and NNS engage in face-to-face interaction with each other.
The data from the competitive interaction experiments reported here support our hypothesis of a competitive "winner-take-all" algorithm that might be used by the auditory system to segregate a sound with a particular periodicity, such as an animal vocalization or a speech sound, from a mixture of simultaneously presented, concurrent sounds.
