Taxonomy generation for document collections

A computer program product comprising a computer usable medium having computer readable program code means embodied in said medium for generating a content taxonomy of a multitude of documents stored on a computer system, said computer readable program code means comprising:

• a subset selector for selecting a subset of said multitude of documents;
• a taxonomy generator for generating a taxonomy for said subset, wherein said taxonomy generator further comprises a first-feature-extractor for extracting for each document of said subset its features, and for computing its feature statistics in a feature-vector as a representation of said document;
• and
• a routing selector for computing, for each unprocessed document of said multitude of documents not belonging to said subset, similarities with said outer-clusters and for assigning said document to the leaf-node of said taxonomy-hierarchy being the outer-cluster with largest similarity,
• wherein said taxonomy is a tree-structured taxonomy-hierarchy, and
• wherein said subset is divided into a set of clusters with largest intra-similarity, and
• wherein each of said clusters of largest intra-similarity is assigned to a leaf-node of said taxonomy-hierarchy as outer-clusters, and
• wherein inner-nodes of said taxonomy-hierarchy order said subset, starting with said outer-clusters, into inner-clusters with increasing cluster size and decreasing similarity.

A system for generating a content taxonomy of a multitude of documents stored on a computer system, said system comprising:

• means for selecting a subset of said multitude of documents;
• means for generating a taxonomy for said subset,
• wherein said taxonomy is a tree-structured taxonomy-hierarchy, and
• wherein said subset is divided into a set of clusters with largest intra-similarity, and
• wherein each of said clusters of largest intra-similarity is assigned to a leaf-node of said taxonomy-hierarchy as outer-clusters, and
• wherein inner-nodes of said taxonomy-hierarchy order said subset, starting with said outer-clusters, into inner-clusters with increasing cluster size and decreasing similarity, and
• wherein said means for generating further comprises a first-feature-extractor means for extracting for each document of said subset its features, and for computing its feature statistics in a feature-vector as a representation of said document;
• and
• means for computing, for each unprocessed document of said multitude of documents not belonging to said subset, similarities with said outer-clusters, and for assigning said document to the leaf-node of said taxonomy-hierarchy being the outer-cluster with largest similarity.