1. A computer-implemented method, comprising: identifying, for a first item of a plurality of items, at least one item category associated with the first item and at least one second item; determining, by a computer system, a plurality of attributes common to the identified at least one item category based at least in part on identifying the plurality of attributes inherited from at least one parent item category associated with the first item, the at least one parent item category being a parent node to a child node associated with the at least one item category associated with the first item and the at least one second item in a browse-node hierarchy; identifying at least one attribute of the plurality of attributes that is not populated for the first item; extracting, from the at least one second item of the plurality of items, a plurality of existing values assigned to the at least one attribute of the plurality of attributes; identifying, from text of the first item, a plurality of candidate values, the plurality of candidate values comprising at least one candidate value for the at least one attribute of the plurality of attributes; associating a set of priority indicators with the plurality of candidate values, the set of priority indicators generated based at least in part on pre-determined rules that utilize a context associated with a candidate value of the plurality of candidate values to represent importance of the candidate value in comparison to other potential candidate values, the context based at least in part on a set of candidate values of the plurality of candidate values identified by the pre-determined rules that are associated with a position of a given candidate value within the text; implementing a rule engine that implements a rule set specified by a user to iteratively alter the rule set after removing one or more candidate values of the plurality of candidate values to prioritize remaining candidate values of the plurality of candidate values based at least in part on the set of priority indicators; filtering the prioritized remaining candidate values from the rule engine to determine a potential value based at least in part on the plurality of existing values associated with the at least one attribute of the plurality of attributes and the prioritized remaining candidate values; and populating, by the computing system, the at least one attribute of the plurality of attributes of the first item with the potential value.
2. The computer-implemented method of claim 1 , wherein the plurality of attributes common to the identified category is determined by extracting attributes from multiple second items of the plurality of items, each of the multiple second items associated with the identified category.