US 2020/0401663 A1 · Techniques for Generating a Topic Model

Abstract

In some examples, a system for generating a topic model includes a processor that can process a set of documents to generate training data, wherein each document in the set of documents is associated with one or more users. The processor can also generate a plurality of topic models using the training data, such that each topic model includes a different number of topics. The processor can also generate an evaluation score for each of the topic models based on information about the users associated with the documents included in the training data. The evaluation score describes a percentage of topics that exhibit a specified level of interest from a specified number of users. The processor can also identify a final topic model based on the evaluation scores and store the final topic model to be used in natural language processing.

Claims20

Dependent claims

A system for generating a topic model comprising:

a processor to:
process a set of documents to generate training data, wherein each document in the set of documents is associated with one or more users;
generate a plurality of topic models using the training data, wherein each topic model comprises a different number of topics;
generate an evaluation score for each of the plurality of topic models based on information about the users associated with the documents included in the training data, wherein the evaluation score describes a percentage of topics that exhibit a specified level of interest from a specified number of users;
identify a final topic model based on the evaluation scores and store the final topic model to be used in natural language processing.

2 more elements

A computer program product for executing natural language processing techniques comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, and wherein the program instructions are executable by a processor to cause the processor to:

process a set of documents to generate training data, wherein each document in the set of documents is associated with one or more users;
generate a plurality of topic models using the training data, wherein each topic model comprises a different number of topics;
generate a user-referenced criterion for each of the plurality of topic models based on information about the users associated with the documents included in the training data, wherein the evaluation score describes a percentage of topics that exhibit a specified level of interest from a specified number of users;
identify a final topic model based on the user-referenced criterion and store the final topic model to be used in natural language processing.

1 more element

Dependencies are inferred from the claim text.

Techniques for Generating a Topic Model

Life of this patent

Techniques for Generating a Topic Model

Life of this patent

Abstract

Claims20