Duplicate from t-tech/T-ECD

Co-authored-by: Kirill Lyahnovich <kliakhnovich@users.noreply.huggingface.co>

README.md

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+---
+license: cc-by-nc-sa-4.0
+tags:
+- recsys
+- e-commerce
+- retrieval
+- dataset
+- ranking
+- cross-domain
+language:
+- ru
+- en
+size_categories:
+- 100B<n<1T
+pretty_name: T-ECD
+---
+
+
+# T-ECD: T-Tech E-commerce Cross-Domain Dataset
+
+![image (2)](https://cdn-uploads.huggingface.co/production/uploads/645d4947f5760d1530d55023/t8w2QTQbnH0DhEIbJYCnT.png)
+
+⭐️ **T-ECD** is a large-scale synthetic cross-domain dataset for recommender systems research, created by T-Bank's RecSys R&D team. 
+It captures real-world e-commerce interaction patterns across multiple domains while ensuring complete anonymity through synthetic generation.
+
+🎯 Overview
+T-ECD represents user interactions across five different e-commerce domains within a banking ecosystem:
+
+- **Marketplace** — browsing and interacting with items in an e-commerce marketplace.  
+- **Retail** — interactions within a retail delivery service, including cart additions and completed orders.  
+- **Payments** — online and offline financial transactions between users and brands.  
+- **Offers** — responses to promotional content such as impressions, clicks, and partner transitions.  
+- **Reviews** — explicit user feedback in the form of ratings and embeddings of textual comments.  
+
+**Scale:**  
+- **~135B** interactions  
+- ~44M users  
+- ~30M items  
+- **1300+ days of temporal coverage**  
+
+
+Additionally, we provide **T-ECD Small** - a compact version containing 1B interactions that excludes the Payments domain.
+
+<div style="font-size: 1.1em;">
+
+| Metric | T-ECD Small | T-ECD Full |
+|--------|-------------|------------|
+| 🔄 **Interactions** | ~1B | **~135B** |
+| 👥 **Users** | ~3.5M | **~44M** |
+| 📦 **Items** | ~2.6M | **~30M** |
+| 🏪 **Brands** | ~29K | **~1M** |
+| 📅 **Temporal Coverage** | 200+ days | **1300+ days** |
+| 🌐 **Domains** | 4 (excl. Payments) | **5 (all domains)** |
+
+</div>
+
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/645d4947f5760d1530d55023/Y3hHv_cipdq2p4A9jiQoz.png" style="max-width: 80%; height: auto;">
+
+
+Cross-domain consistency is achieved by aligning identifiers across all domains:  
+- the same `user_id` always refers to the same individual user, and  
+- the same `brand_id` always refers to the same brand entity.  
+
+This alignment allows researchers to seamlessly link interactions from different services, enabling studies in transfer learning, cross-domain personalization, and multi-task modeling.
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/645d4947f5760d1530d55023/QG0DavvcvccN1GcN_gRL6.png" style="max-width: 80%; height: auto;">
+<img src="https://cdn-uploads.huggingface.co/production/uploads/645d4947f5760d1530d55023/s8a8iC4RmUjsD_hzOVPvD.png" style="max-width: 80%; height: auto;">
+
+---
+
+### 📂 Data Schema
+
+The dataset is stored in **Parquet** format with daily partitions (`{day}`).  
+The directory structure is as follows:
+
+```
+t-ecd/
+├── users.pq
+├── brands.pq
+├── marketplace/
+│ ├── events/{day}.pq
+│ └── items.pq
+├── retail/
+│ ├── events/{day}.pq
+│ └── items.pq
+├── payments/
+│ ├── events/{day}.pq
+│ └── receipts/{day}.pq
+├── offers/
+│ ├── events/{day}.pq
+│ └── items.pq
+└── reviews/{day}.pq
+```
+
+#### Data availability
+<img src="https://cdn-uploads.huggingface.co/production/uploads/645d4947f5760d1530d55023/c2Clc9bNxL9i7jgGBfBq2.png" style="max-width: 80%; height: auto;" alt="Temporal distribution of events over domains">
+*Temporal distribution of events over domains*
+In line with real-world industrial environments, domain-specific data availability varies in historical depth. 
+This reflects practical constraints including data retention policies and product lifecycle stages - 
+newer e-commerce services naturally have shorter histories compared to established banking domains like payments and transactions.
+
+
+### ⚙️ Events and Catalogs
+
+- **Events**: Each domain provides logs of user interactions with the following possible columns:
+
+  - `action_type` — interaction type (e.g., view, click, add-to-cart, order, transaction).  
+  - `subdomain` — surface where the interaction occurred (recommendations, catalog, search, checkout, campaign); available in Marketplace and Retail.  
+  - `item_id` — present in Marketplace, Retail, and Offers; identifies a specific product or offer.  
+  - `brand_id` — present in all domains; denotes the seller, store, or partner associated with an item, offer, or transaction.  
+  - `price` —  represents the monetary value of the interaction.
+  - `count` — represents the amount of items in single interaction.
+  - `os` — user operating system, available in Marketplace and Retail.
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/645d4947f5760d1530d55023/Q7aeb_I-Yf-rcqyPDTOLa.png" style="max-width: 80%; height: auto;" >
+
+- **Item catalogs (`items.pq`)**: Available for Marketplace, Retail, and Offers. Each entry includes:  
+  - `item_id`  
+  - `brand_id`  
+  - category information (if available)  
+  - pretrained embedding (if available)  
+
+- **User catalog (`users.pq`)**: Contains anonymized user attributes such as region and socio-demographic cluster.  
+
+- **Brand catalog (`brands.pq`)**: Contains `brand_id`, brand-level metadata, and embeddings.  
+
+#### 🧾 Special Structures
+
+- **Receipts (`payments/receipts/{day}.pq`)**:  
+  Some transactions include detailed receipts with purchased items, their quantities, and prices.  
+  Items are aligned with Marketplace and Retail catalogs, enabling fine-grained cross-domain linkage at the product level.  
+
+- **Reviews (`reviews/{day}.pq`)**:  
+  Provide explicit ratings per brand.  
+  Raw text reviews are not included; instead, we release pretrained text embeddings to preserve privacy while enabling multimodal research.  
+---
+
+### 🛠️ Data Collection
+
+T-ECD was generated through a multi-step process:  
+1. **Sampling of event chains**: sequences of interactions were sampled from real logs of T-Bank ecosystem services.  
+2. **Anonymization**: user and brand identifiers were pseudonymized; sensitive attributes removed.  
+3. **Synthetic generation**: based on real distributions and event patterns, new synthetic interaction chains were produced, preserving structural properties such as sparsity, heavy tails, cross-domain overlaps, and behavioral contexts.  
+
+This process ensures that the dataset is privacy-preserving while remaining representative of industrial recommender system data.  
+
+## ⚠️ Important Note on Temporal Data Usage
+
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/645d4947f5760d1530d55023/zaPAcuD3CItTzP2PBkErs.png" style="max-width: 80%; height: auto;">
+
+
+**To prevent data leakage, events from the final 12 hours should not be used for prediction tasks.** 
+The dataset contains temporal noise that requires maintaining a minimum 12-hour gap between the timestamp of the most recent user event and the prediction timestamp.
+This constraint applies to both training and testing scenarios to avoid temporal data leakage.
+
+
+## Download
+
+#### Basic Download
+
+```python
+from huggingface_hub import snapshot_download
+
+snapshot_download(
+    repo_id="t-tech/T-ECD",
+    repo_type="dataset",
+    allow_patterns="dataset/full/",
+    local_dir="./t_ecd_data",
+    token="<your_hf_token>" 
+)
+```
+
+
+#### Selective Download
+
+For advanced usage including selection of domains and date ranges we provide custom downloader [tecd_downloader.py](https://huggingface.co/datasets/t-tech/T-ECD/blob/main/tecd_downloader.py)
+
+Example usage:
+
+```python
+from tecd_downloader import download_dataset
+
+download_dataset(
+    token="<your_hf_token>",
+    dataset_path="dataset/small",
+    local_dir="t_ecd_small_partial",
+    domains=["retail", "marketplace"],
+    day_begin=1300,
+    day_end=1308,
+    max_workers=10
+)
+```
+
+
+---
+
+### 🔐 License
+
+This dataset is released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0) licence
+
+
+---

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