Patent ID: 11886515
Assignee: THOMSON REUTERS ENTERPRISE CENTRE GMBH
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method, comprising:
generating, using a processor, a similarity matrix or a co-occurrence matrix for a corpus of documents;
applying, using the processor, a clustering algorithm to the similarity matrix or the co-occurrence matrix to generate a graph corresponding to the corpus of documents;
applying, using the processor, a community detection algorithm to the graph to detect a plurality of clusters of nodes of the graph, the plurality of clusters having a first modularity score exceeding a minimum modularity threshold;
for a first cluster of the plurality of clusters, iteratively removing, using the processor, a node of the first cluster to transform the first cluster into a second cluster based on a pruning stop criterion, wherein the removed node has associated therewith a betweenness centrality that is a maximum of betweenness centralities of remaining nodes of the second cluster;
applying, using the processor, the community detection algorithm to the second cluster to identify a plurality of third clusters of the second cluster, the plurality of third clusters having a second modularity score exceeding the minimum modularity threshold;
presenting, using the processor, the plurality of third clusters as a taxon graph composed of taxon nodes each representing one of the plurality of third clusters;
receiving, at the processor, a first document for labeling;
defining, using the processor, a first probability distribution associated with the first document and second probability distributions associated with the taxon nodes; and
extracting a label from the taxon nodes for labeling the first document based on a statistical distance between the first probability distribution and the second probability distributions.