Abstract: A computing system generates a taxonomic tree for a domain in an unsupervised manner (e.g., without human intervention). Hierarchical structures of documents of the domain are collected from a document index. A category for each node of each of the hierarchical structures is extracted. The extracted categories are embedded as multidimensional category vectors in a multidimensional vector space. The multidimensional category vectors are grouped into multiple groups. The multidimensional category vectors of a first group satisfy a similarity condition for the first group better than the multidimensional category vectors of a second group. Each group of the multidimensional category vectors constitutes a category cluster. Each category cluster includes multidimensional category vectors for extracted categories from different hierarchical levels of the hierarchical structures. The taxonomic tree is generated with each category cluster inserted as a category node of the taxonomic tree.

Abstract: A computing system generates a taxonomic tree for a domain in an unsupervised manner (e.g., without human intervention). Hierarchical structures of documents of the domain are collected from a document index. A category for each node of each of the hierarchical structures is extracted. The extracted categories are embedded as multidimensional category vectors in a multidimensional vector space. The multidimensional category vectors are grouped into multiple groups. The multidimensional category vectors of a first group satisfy a similarity condition for the first group better than the multidimensional category vectors of a second group. Each group of the multidimensional category vectors constitutes a category cluster. Each category cluster includes multidimensional category vectors for extracted categories from different hierarchical levels of the hierarchical structures. The taxonomic tree is generated with each category cluster inserted as a category node of the taxonomic tree.