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Aspect Based ReDial(AB-ReDial): Is a subset data from ReDial annotated on six dialogue aspects and overall user satisfaction at the turn and dialogue levels with the following aspects; relevance, interestingness, understanding, task completion, interest arousal, and efficiency

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Understanding and Predicting User Satisfaction with Conversational Recommender Systems

This repository consist of resources created for the following paper:

    Understanding and Predicting User Satisfaction with Conversational Recommender Systems

Dataset Description

ABA-ReDial is as subset of the ReDial dataset with additional annotations at the turn and dialogue levels for several aspects.

Turn-level Annotation

At the turn level we annotate each turn with two dialogue aspects: relevance and interestingness and turn-level satisfaction. This data is in the file annotated_turns.csv.

Each turn consist of four utterances: two previous utterances as context, current utterance(system utterance) and the next user utterance.

The labels are relevanceK, interestingessK and overallK, where K is the turn number.

Each turn was annotated with atleast three annotators.

Dialogue-level Annotation

At the Dialogue level, a dialogues is annotated on four dialogue aspects namely: understanding, task completion, interest arousal, and efficiency and finally overall user satisafction for each turn is annotated. This data is in the file annotated_dialogues.csv

Each dialogue was annotated by atleast three annotated, and each dialogue has a unque ConvId. A dialogue annotated by multiple annotators share the same unique Id.

Turns sampled from the same dialogue share a unique Id with each other and the dialogue.

Dataset Statistics

level count
Turns 600
Dialogues 200

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Aspect Based ReDial(AB-ReDial): Is a subset data from ReDial annotated on six dialogue aspects and overall user satisfaction at the turn and dialogue levels with the following aspects; relevance, interestingness, understanding, task completion, interest arousal, and efficiency

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