Recursive agglomerative clustering of time-structured communications

A system, comprising:

• a memory;
• and
• a processor coupled to the memory, wherein the processor is configured to:
• select a current document cluster of a plurality of document clusters, wherein the current document cluster includes documents organized according to a predefined algorithm based on respective distances between vectorized representations of the respective documents within the current document cluster;
• based on a vector representing the current document cluster, identify a sorted list of terms associated with the current document cluster, wherein respective terms of the sorted list of terms are weighted according to a Term Frequency-Inverse Document Frequency (TF-IDF) weighting scheme;
• initialize a label associated with the current document cluster;
• automatically select a first term from the list of terms comprised by the documents of the document cluster, based on respective weightings of the terms according to the term frequency-inverse document frequency (TF-IDF) weighting scheme;
• automatically append the term to the label associated with the current document cluster;
• responsive to determining that the label is found in a label dictionary, (i) iteratively select one or more next terms from the list of terms comprised by the document cluster based on the respective weightings of the terms according to the TF-IDF weighting scheme and (ii) automatically append each of the next terms to the label associated with the current document cluster;
• responsive to failing to locate the label in the label dictionary, insert the label into the label dictionary;
• and
• associate the label with the current document cluster.

A non-transitory, computer-readable storage medium comprising executable instructions that, when executed by a computer system, cause the computer system to:

• select a current document cluster of a plurality of document clusters, wherein the current document cluster includes documents organized according to a predefined algorithm based on respective distances between vectorized representations of the respective documents within the current document cluster;
• based on a vector representing the current document cluster, identify a sorted list of terms associated with the current document cluster, wherein respective terms of the sorted list of terms are weighted according to a Term Frequency-Inverse Document Frequency (TF-IDF) weighting scheme;
• initialize a label associated with the current document cluster;
• automatically select a first term from the list of terms comprised by the documents of the document cluster, based on respective weightings of the terms according to the term frequency-inverse document frequency (TF-IDF) weighting scheme;
• automatically append the term to the label associated with the current document cluster;
• responsive to determining that the label is found in a label dictionary, (i) iteratively select one or more next terms from the list of terms comprised by the document cluster based on the respective weightings of the terms according to the TF-IDF weighting scheme and (ii) automatically append each of the next terms to the label associated with the current document cluster;
• responsive to failing to locate the label in the label dictionary, insert the label into the label dictionary;
• and
• associate the label with the current document cluster.