E-commerce
Introduced by Zhang et al. in Modeling Multi-turn Conversation with Deep Utterance Aggregation
We release E-commerce Dialogue Corpus, comprising a training data set, a development set and a test set for retrieval based chatbot. The statistics of E-commerical Conversation Corpus are shown in the following table.
| Train | Val | Test | |
|---|---|---|---|
| Session-response pairs | 1m | 10k | 10k |
| Avg. positive response per session | 1 | 1 | 1 |
| Min turn per session | 3 | 3 | 3 |
| Max ture per session | 10 | 10 | 10 |
| Average turn per session | 5.51 | 5.48 | 5.64 |
| Average Word per utterance | 7.02 | 6.99 | 7.11 |
The full corpus can be downloaded from https://drive.google.com/file/d/154J-neBo20ABtSmJDvm7DK0eTuieAuvw/view?usp=sharing.
Benchmarks
| Trend | Task | Dataset Variant | Best Model | Paper | Code |
|---|---|---|---|---|---|
|
E-commerce
|
Dial-MAE
|
Papers
| Paper | Code | Results | Date | Stars |
|---|
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