Conversational aspect sentiment analysis for dialogue understanding

An apparatus for sentiment analysis for multi-turn conversations, the apparatus comprising:

• at least one memory configured to store computer program code;
• at least one processor configured to access the computer program code and operate as instructed by the computer program code, the computer program code including:
• first obtaining code configured to cause the at least one processor to obtain input dialogue;
• first extracting code configured to cause the at least one processor to extract at least one sentiment expression based on sentence embeddings corresponding to the input dialogue;
• first generating code configured to cause the at least one processor to generate polarity values based on the sentence embeddings corresponding to the input dialogue;
• and
• first determining code configured to cause the at least one processor to, subsequent to determining the polarity values, determine a target mention associated with the input dialogue based on the at least one sentiment expression and the sentence embeddings, wherein the first determining code comprises:
• second generating code configured to cause the at least one processor to generate rich contextual representations based on a concatenation of turn-wise distances on the sentence embeddings, the speaker information on the sentence embeddings, and the at least one sentiment expression, wherein the speaker information indicates whether the input dialogue are from a same speaker;
• and
• second determining code configured to cause the at least one processor to determine the target mention based on calculated boundaries, wherein the calculated boundaries are generated using the rich contextual representations.

A non-transitory computer readable medium storing a program causing a computer to execute a process, the process comprising:

• obtaining input dialogue;
• extracting at least one sentiment expression based on sentence embeddings corresponding to the input dialogue;
• generating polarity values based on the sentence embeddings corresponding to the input dialogue;
• and
• subsequent to determining the polarity values, determining a target mention associated with the input dialogue based on the at least one sentiment expression and the sentence embeddings,
• wherein the determining of the target mention comprises:
• generating rich contextual representations based on a concatenation of turn-wise distances on the sentence embeddings, the speaker information on the sentence embeddings, and the at least one sentiment expression, wherein the speaker information indicates whether the input dialogue are from a same speaker;
• and
• determining the target mention based on calculated boundaries, wherein the calculated boundaries are generated using the rich contextual representations.