Abstract: Various embodiments are provided herein for systems and methods for real-time, or near real-time, multi-dimensional ranking of experts. In at least one embodiment, receiving one or more evaluation datasets; for each given evaluation dataset, associating the evaluation dataset with: (i) at least one evaluation data category, (ii) at least one taxonomy category, and (iii) at least one expert of the plurality of experts; subsequently, receiving one or more search filter criteria for ranking at least a subset of the plurality of experts; generating a ranking of the at least subset of the plurality of experts, wherein the ranking is based on the search filter criteria, and is further generated based on the associations determined for each evaluation dataset; and displaying, on a user interface, at least a portion of the plurality of rankings as the multi-dimensional ranking of the plurality of experts.

Abstract: Various embodiments are provided herein for systems and methods for real-time, or near real-time, multi-dimensional ranking of experts. In at least one embodiment, receiving one or more evaluation datasets; for each given evaluation dataset, associating the evaluation dataset with: (i) at least one evaluation data category, (ii) at least one taxonomy category, and (iii) at least one expert of the plurality of experts; subsequently, receiving one or more search filter criteria for ranking at least a subset of the plurality of experts; generating a ranking of the at least subset of the plurality of experts, wherein the ranking is based on the search filter criteria, and is further generated based on the associations determined for each evaluation dataset; and displaying, on a user interface, at least a portion of the plurality of rankings as the multi-dimensional ranking of the plurality of experts.