Systems and methods for agglomerative clustering

A computerized system for clustering nodes, the system comprising:

• a memory, and
• a computer processor configured to:
• calculate a distance between nodes for each of a plurality of pairs of nodes, the pairs comprising one or more of a plurality of entities and initial clusters;
• select one or more of the pairs based on the calculated distances;
• and
• merge one or more of the selected pairs including a common node into one or more final clusters.

A method for categorizing interactions using an automatically generated domain taxonomy, the method comprising:

• in a computerized system comprising a processor and a memory, and connected by a network to one or more remote computers:
• extracting, by the processor, a plurality of words from one or more documents;
• calculating, by the processor, a distance between nodes for each of a plurality of pairs of nodes, the pairs comprising one or more of the words and initial clusters;
• selecting, by the processor, one or more of the pairs based on the calculated distances;
• merging, by the processor, one or more of the selected pairs including a common node into one or more final clusters;
• ranking, by the processor, one or more nodes within one or more of the final clusters;
• selecting, by the processor, one or more of the ranked nodes as cluster titles;
• iteratively repeating the extracting of a plurality of words, the calculating of a distance between nodes, the selecting one or more of the pairs, the merging of one or more of the selected pairs, the ranking of one or more nodes, and the selecting of one or more of the ranked notes, until one or more convergence criteria are met, wherein the criteria based on at least one of:
• a maximum cluster size, and a maximum number of pairs including a common node;
• and
• automatically generating a taxonomy comprising one or more of the clusters and the titles from one or more iterations, the taxonomy organized in a hierarchical structure.