OPTIMIZING RESOURCE ALLOCATION TO A BID REQUEST RESPONSE BASED ON COGNITIVE ANALYSIS OF NATURAL LANGUAGE DOCUMENTATION
Abstract:
Approaches presented herein enable optimizing resource allocation to a bid request response based on a cognitive analysis of natural language artifacts. More specifically, a bid request and a plurality of supporting artifacts in a natural language are obtained. A cognitive analysis of the request and supporting artifacts is performed to extract a set of information entities. The extracted information entities are normalized using a lexical-relations based graph database to classify the set of extracted information entities as standardized concepts. A subset of the set of the standardized concepts is identified as a set of parameters corresponding to a set of predetermined variables. Each variable of the set of predetermined variables is weighted according to a likelihood that the variable indicates a relevance of a resource. A probability that a particular resource is relevant is determined based on the weighting and that resource is assigned to the bid request response.
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