Identifying text for labeling utilizing topic modeling-based text clustering

A computer program product comprising a computer readable storage medium having stored thereon:

• program instructions to receive a set of unlabeled input text for classification with respect to a particular domain, wherein the domain includes a labeled corpus for which topics of a set of topics correspond to labels from the corpus, and wherein the topics include statistical probability distributions of words in the corpus;
• program instructions to perform topic modeling on the input text to associate portions of the input text with respective classifications, wherein the classifications include statistical probability distributions of topics of the set of topics in the respective portions of the input text, and wherein the classifications reflect amounts of each topic of the set of topics that are present in the respective portions of the input text;
• and
• program instructions to apply a machine learning-based selection strategy to the portions of the input text and their respective classifications to identify one or more portions of the input text for labeling.

A computer system comprising:

• a processor(s) set;
• and
• a computer readable storage medium;
• wherein:
• the processor set is structured, located, connected and/or programmed to run program instructions stored on the computer readable storage medium;
• and
• the program instructions include:
• program instructions to receive a set of unlabeled input text for classification with respect to a particular domain, wherein the domain includes a labeled corpus for which topics of a set of topics correspond to labels from the corpus, and wherein the topics include statistical probability distributions of words in the corpus;
• program instructions to perform topic modeling on the input text to associate portions of the input text with respective classifications, wherein the classifications include statistical probability distributions of topics of the set of topics in the respective portions of the input text, and wherein the classifications reflect amounts of each topic of the set of topics that are present in the respective portions of the input text;
• and
• program instructions to apply a machine learning-based selection strategy to the portions of the input text and their respective classifications to identify one or more portions of the input text for labeling.