Computer-Implemented Systems and Methods for Taxonomy Development

A computer-implemented system for generating a set of classifiers, comprising:

• one or more data processors;
• a computer-readable medium encoded with instructions for commanding the one or more data processors to execute steps including:
• determining one or more locations of instances of a topic term in a collection of documents;
• identifying one or more topic term phrases by parsing words in the collection of documents, wherein a topic term phrase includes one or more words that appear within a topic threshold distance of a topic term;
• identifying one or more sentiment terms within a topic term phrase;
• identifying one or more candidate classifiers by parsing words in the one or more topic term phrases, wherein a candidate classifier is a word that appears within a sentiment threshold distance of a sentiment term;
• generating a colocation matrix including a plurality of rows, wherein a candidate classifier is associated with a row, and wherein the colocation matrix is generated using the locations of the candidate classifiers as they appear within the collection of documents;
• identifying a seed row, wherein the seed row is selected from among the plurality of rows, and wherein the seed row is associated with a particular attribute;
• determining distance metrics by comparing rows of the colocation matrix to the seed row;
• and
• generating a set of classifiers for the particular attribute, wherein classifiers in the set of classifiers are selected using the distance metrics.

A computer-readable medium encoded with instructions for commanding one or more data processors to execute method for generating a set of classifiers, the method comprising:

• determining one or more locations of instances of a topic term in a collection of documents;
• identifying one or more topic term phrases by parsing words in the collection of documents, wherein a topic term phrase includes one or more words that appear within a topic threshold distance of a topic term;
• identifying one or more sentiment terms within a topic term phrase;
• identifying one or more candidate classifiers by parsing words in the one or more topic term phrases, wherein a candidate classifier is a word that appears within a sentiment threshold distance of a sentiment term;
• generating a colocation matrix including a plurality of rows, wherein a candidate classifier is associated with a row, and wherein the colocation matrix is generated using the locations of the candidate classifiers as they appear within the collection of documents;
• identifying a seed row, wherein the seed row is selected from among the plurality of rows, and wherein the seed row is associated with a particular attribute;
• determining distance metrics by comparing rows of the colocation matrix to the seed row;
• and
• generating a set of classifiers for the particular attribute, wherein classifiers in the set of classifiers are selected using the distance metrics.