Query-focused extractive text summarization of textual data

An apparatus comprising at least one processor and at least one memory comprising computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:

• receive an input data object comprising textual data of a conversation, wherein the textual data comprises a plurality of sentence-level tokens and each sentence-level token comprises one or more word-level tokens;
• generate and assign an interrogative classification for one or more sentence-level tokens of the plurality of sentence-level tokens, wherein the interrogative classification is determined based at least in part on evaluating the one or more word-level tokens of a sentence-level token;
• identify one or more subtopic portions of the textual data, wherein each subtopic portion comprises a portion of the plurality of sentence-level tokens and at least one interrogative sentence-level token, and wherein each interrogative sentence-level token is located within one subtopic portion;
• for each interrogative sentence-level token, determine whether the interrogative sentence-level token is substantially similar to a target query of a plurality of target queries;
• for each particular interrogative sentence-level token determined to be substantially similar to a target query, select one or more sentence-level tokens in a subtopic portion corresponding to the particular interrogative sentence-level token;
• generate a summarization data object comprising the selected one or more sentence-level tokens for each particular interrogative sentence-level token determined to be substantially similar to a target query;
• and
• perform one or more summarization-based actions based at least in part on the summarization data object.

A computer program product comprising at least one computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising executable portions configured to cause at least one processor to:

• receive an input data object comprising textual data of a conversation, wherein the textual data comprises a plurality of sentence-level tokens and each sentence-level token comprises one or more word-level tokens;
• generate and assign an interrogative classification for one or more sentence-level tokens of the plurality of sentence-level tokens, wherein the interrogative classification is determined based at least in part on evaluating the one or more word-level tokens of a sentence-level token;
• identify one or more subtopic portions of the textual data, wherein each subtopic portion comprises a portion of the plurality of sentence-level tokens and at least one interrogative sentence-level token, and wherein each interrogative sentence-level token is located within one subtopic portion;
• for each interrogative sentence-level token, determine whether the interrogative sentence-level token is substantially similar to a target query of a plurality of target queries;
• for each particular interrogative sentence-level token determined to be substantially similar to a target query, select one or more sentence-level tokens in a subtopic portion corresponding to the particular interrogative sentence-level token;
• generate a summarization data object comprising the selected one or more sentence-level tokens for each particular interrogative sentence-level token determined to be substantially similar to a target query;
• and
• perform one or more summarization-based actions based at least in part on the summarization data object.