US 2022/0092096 A1 · AUTOMATIC GENERATION OF SHORT NAMES FOR A NAMED ENTITY

Abstract

Embodiments of the present disclosure present and approach for automatic generation of short names for a named entity. According to the approach, a standard text segment is obtained, which indicates a full name of a named entity. At least one feature representation of the standard text segment is extracted. A plurality of variant text segments are generated based on the at least one feature representation using a generative learning network. The plurality of variant text segments indicate a plurality of short names for the named entity, the generative learning network characterizing a generation of variants for an input text segment. The plurality of variant text segments are stored in association with the standard text segment into a data repository.

Claims20

Dependent claims

A computer-implemented method comprising:

obtaining, by one or more processors, a standard text segment indicating a full name of a named entity;
extracting, by the one the one or more processors, at least one feature representation of the standard text segment;
generating, by the one or more processors, a plurality of variant text segments based on the at least one feature representation using a generative learning network, the plurality of variant text segments indicating a plurality of short names for the named entity, the generative learning network characterizing a generation of variants for an input text segment;
and
storing, by the one or more processors, the plurality of variant text segments in association with the standard text segment into a data repository.

2 more elements

A computer system comprising:

one or more processing units;
and
a memory coupled to the one or more processing units and storing instructions thereon, the instructions, when executed by the one or more processing units, performing acts comprising:
obtaining a standard text segment indicating a full name of a named entity;
extracting at least one feature representation of the standard text segment;
generating, based on the at least one feature representation using a generative learning network, a plurality of variant text segments indicating a plurality of short names for the named entity, the generative learning network characterizing a generation of variants for an input text segment;
and
storing the plurality of variant text segments in association with the standard text segment into a data repository.

5 more elements

A computer program product being tangibly stored on a non-transient machine-readable medium and comprising machine-executable instructions, the instructions, when executed on a device, causing the device to perform acts comprising:

obtaining a standard text segment indicating a full name of a named entity;
extracting at least one feature representation of the standard text segment;
generating, based on the at least one feature representation using a generative learning network, a plurality of variant text segments indicating a plurality of short names for the named entity, the generative learning network characterizing a generation of variants for an input text segment;
and
storing the plurality of variant text segments in association with the standard text segment into a data repository.

2 more elements

Dependencies are inferred from the claim text.

Automatic generation of short names for a named entity

Life of this patent

Automatic generation of short names for a named entity

Life of this patent

Abstract

Claims20