1. A system, comprising a processor configured to: execute a document-oriented search based on a query in an index of documents to generate a set of document results, each document in the set of document results is associated with at least one potential expert; analyze the document results to produce a list of potential experts; calculate an expertise score for each potential expert based on a content score and a metadata score for each potential expert; calculate a confidence score for each potential expert based on a diversity-constrained content score and a diversity-constrained metadata score for each potential expert, wherein the diversity-constrained content score is calculated using an evidence diversity score, comprising a predetermined threshold number of different activities associated with the potential expert, and the content score for the potential expert, the diversity-constrained metadata score is calculated using the evidence diversity score and the metadata score for the potential expert, the content score is calculated based on a number of different content document types and associations associated with the potential expert, the content document types and associations are gathered by parsing websites and stored in a data repository, the metadata score is calculated based on profile-related information associated with the potential expert, and the confidence score is further calculated based on a social score, wherein the processor is configured to generate a graph of connections between the predetermined number of selected experts, the social score for each selected expert is calculated using the graph and based on a number of connections to other selected experts; and send a list of experts with associated confidence scores that are above a confidence score threshold to a client device.
1. A system, comprising a processor configured to: execute a document-oriented search based on a query in an index of documents to generate a set of document results, each document in the set of document results is associated with at least one potential expert; analyze the document results to produce a list of potential experts; calculate an expertise score for each potential expert based on a content score and a metadata score for each potential expert; calculate a confidence score for each potential expert based on a diversity-constrained content score and a diversity-constrained metadata score for each potential expert, wherein the diversity-constrained content score is calculated using an evidence diversity score, comprising a predetermined threshold number of different activities associated with the potential expert, and the content score for the potential expert, the diversity-constrained metadata score is calculated using the evidence diversity score and the metadata score for the potential expert, the content score is calculated based on a number of different content document types and associations associated with the potential expert, the content document types and associations are gathered by parsing websites and stored in a data repository, the metadata score is calculated based on profile-related information associated with the potential expert, and the confidence score is further calculated based on a social score, wherein the processor is configured to generate a graph of connections between the predetermined number of selected experts, the social score for each selected expert is calculated using the graph and based on a number of connections to other selected experts; and send a list of experts with associated confidence scores that are above a confidence score threshold to a client device. 3. The system of claim 1 , wherein the confidence scores are calculated based on preconfigured thresholds.