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--- |
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license: apache-2.0 |
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task_categories: |
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- tabular-classification |
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size_categories: |
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- 100M<n<1B |
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--- |
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We introduce TRACE, the first benchmark dataset for post-click GMV prediction with delayed feedback. |
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📁 Data structure includes: |
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1. **Features**: |
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* **User/Item/Contextual Attributes**: 22 such attributes are provided (e.g., `feature_0` to `feature_21`). |
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* **Click Timestamp**: `click_time`. |
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2. **Labels and Sequence Information**: |
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* **Gross Merchandise Volume (GMV) Sequence**: The sequence of transaction amounts for all purchases associated with a click. This is represented by `dirpay_amt` for the current purchase and `prev_dirpay_amt` for previous purchases. |
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* **Purchase Count Sequence**: The sequence indicating the order of each purchase within the attribution window for a given click. `count` represents the current purchase's order, and `total_counts` indicates the final number of purchases. |
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* **Purchase Timestamp Sequence**: The sequence of timestamps for each purchase. `pay_time` typically represents the timestamp of the current purchase, and `prev_pay_time` contains timestamps of previous purchases. |
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* **Repurchase Indicator (`multi_tag`)**: A binary label (0 or 1) indicating whether the GMV generated by a click is from a single purchase (0) or a repurchase (1). This is derived from the number of purchases. |
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* **Final Ground-Truth GMV Label**: The total GMV accumulated by the end of the attribution window. This is calculated as the sum of `dirpay_amt`. |
