Papers with IntentCapsNet
Zero-shot User Intent Detection via Capsule Neural Networks (D18-1)
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| Challenge: | Existing methods to classify intents are labor-intensive and time-consuming as intents will be diverse and new intents may be involved. |
| Approach: | They propose a zero-shot intent detection problem which aims to detect emerging user intents where no labeled utterances are currently available. |
| Outcome: | The proposed model can discriminate emerging intents when no labeled utterances are available in training data. |
Reconstructing Capsule Networks for Zero-shot Intent Classification (D19-1)
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| Challenge: | Existing methods for intent classification are limited due to fast-emerging intents . a recent study shows that existing methods are not effective in recognizing unseen intents. |
| Approach: | They propose to reconstruct capsule networks for zero-shot intent classification by using latent information from labeled utterances. |
| Outcome: | The proposed method outperforms existing methods on two task-oriented dialogue datasets in different languages. |