Professional services demand fulfillment framework using machine learning
Abstract:
Techniques are described for fulfilling resources demand dynamically. In one example method, a query associated with a request of a demand fulfillment analysis associated with an identification of a plurality of potential persons related to a demand is received. The received query is analyzed to determine an intent of the demand. Based on the determined intent of the demand, algorithms to be applied to an underlying data set are identified, where the underlying data set comprises a collected set of information from a plurality of source systems. The identified algorithms are applied to the underlying data set based on a set of parameters associated with the received query to generate an updated data set from the underlying data set. The updated data set is then clustered to generate a result set from the underlying data set, and a visualization of the result set is generated for presentation.
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