1. A computer implemented method, comprising: identifying a plurality of classification terms indicative of a classification; identifying a corpus of communications from one or more databases, the corpus of communications including a plurality of communications that are not labeled with an association to the classification; determining a cluster of the communications based on occurrence of one or more of the classification terms in the communications of the cluster; subsequent to determining the cluster, determining a feature set based on the communications of the cluster, wherein determining the feature set comprises: determining one or more features that are based on content that appears in a plurality of the communications of the cluster, wherein the content is in addition to the classification terms used in determining the cluster, and wherein determining the features based on the content that is in addition to the classification terms comprises determining the features based on the content appearing in the plurality of the communications of the cluster; assigning the feature set to an indication of the classification; and using the assigned feature set to classify an additional communication with the classification or using the assigned feature set to select a data extraction parser, for the classification, for the additional communication.
1. A computer implemented method, comprising: identifying a plurality of classification terms indicative of a classification; identifying a corpus of communications from one or more databases, the corpus of communications including a plurality of communications that are not labeled with an association to the classification; determining a cluster of the communications based on occurrence of one or more of the classification terms in the communications of the cluster; subsequent to determining the cluster, determining a feature set based on the communications of the cluster, wherein determining the feature set comprises: determining one or more features that are based on content that appears in a plurality of the communications of the cluster, wherein the content is in addition to the classification terms used in determining the cluster, and wherein determining the features based on the content that is in addition to the classification terms comprises determining the features based on the content appearing in the plurality of the communications of the cluster; assigning the feature set to an indication of the classification; and using the assigned feature set to classify an additional communication with the classification or using the assigned feature set to select a data extraction parser, for the classification, for the additional communication. 20. The computer implemented method of claim 1 , wherein determining the feature set further comprises: determining a weight, for given content of the content, based on a quantity, of the communications of the cluster, in which the given content appears; and based on the weight satisfying a threshold: including a given feature that corresponds to the given content in the feature set, the given feature being one of the features.