Update README.md

README.md

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-license: cc-by-nc-sa-4.0
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+---
+license: cc-by-nc-sa-4.0
+---
+
+## Dataset Description
+
+The **RealMedConv** dataset consists of anonymized, real-world dialogues between licensed pharmacists and users seeking over-the-counter (OTC) medication advice. Each conversation is goal-oriented: the pharmacist gathers sufficient symptom information to provide an online and appropriate recommendation. Dialogues are typically concise, spanning 3–5 turns, reflecting the efficient and expert-driven nature of professional medical consultations.
+
+This dataset originates from real user-pharmacist interactions on an Alibaba Group service platform. To ensure strict compliance with data privacy and security standards, the raw logs have undergone rigorous processing—including de-identification, filtering, translation, and controlled perturbation—so that *no personally identifiable information (PII) or sensitive content remains*. The released version poses *no privacy leakage or security risks*.
+
+Only a small subset is being open-sourced to support academic research, particularly in the area of **goal-directed, proactive dialogue systems for healthcare advisory tasks**.
+
+---
+
+## Intended Uses & Limitations
+
+### Intended Uses
+- Research on **task-oriented dialogue systems**, especially those requiring *information-gathering strategies* and *online recommendation logic*.
+- Development and evaluation of **proactive conversational agents** in health-related contexts.
+- Benchmarking models on **symptom inquiry efficiency**, **user intent understanding**, and **risk-aware response generation**.
+
+### Limitations
+- **Not for clinical use**: This dataset is strictly for **non-clinical, academic research**. It does **not** constitute medical advice, nor should it be used to train systems intended for real-world diagnosis or treatment.
+- **Limited disease scope**: Only conversations related to *20 common, non-severe conditions* (selected from a broader set, with hundreds of conditions) are included.
+- **Machine-Translated English**: All dialogues were originally in Chinese and have been *machine-translated into English*; minor stylistic or semantic artifacts may exist.
+- **Actual medication names are withheld**: The `<med_search>` token indicates where a recommendation would be generated, but specific drug names or dosages are **not included** in the public release.
+
+---
+
+## License
+
+This dataset is released under the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)** license.
+
+- ✅ **You are free to**:
+- Share — copy and redistribute the material in any medium or format.
+- Adapt — remix, transform, and build upon the material.
+- ❌ **Under the following terms**:
+- **Attribution** — You must give appropriate credit, provide a link to the license, and indicate if changes were made.
+- **NonCommercial** — You may not use the material for commercial purposes.
+- **ShareAlike** — If you remix, transform, or build upon the material, you must distribute your contributions under the **same license** (CC BY-NC-SA 4.0 or a compatible one).
+
+🔗 License URL: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.en
+
+> **Note**: In addition to this license, users are required to agree to a separate **Data Use Commitment Agreement** at download time, affirming responsible and ethical usage.
+
+---
+
+## Data Processing & Privacy Safeguards
+
+To protect user privacy and prevent model inversion or re-identification, the following measures were applied:
+
+1. **Strict De-identification**: All PII (e.g., names, ID numbers, phone numbers) was removed from raw logs.
+2. **Temporal Perturbation**: Any residual temporal markers (e.g., birth months) were perturbed to prevent linkage attacks.
+3. **Controlled Sampling**: Only 2,000 sessions covering 20 representative conditions were selected—insufficient to reconstruct or replicate the full-scale production model.
+4. **Translation & Style Normalization**: Original Chinese dialogues were translated into English using internal models, with conversational style harmonized for consistency.
+
+---
+
+## Dataset Structure
+
+The dataset is provided in JSONL format with two splits, `train.jsonl` and `test.jsonl`.
+
+Each entry contains:
+- `session_id`: Anonymized session identifier (integer)
+- `diagn`: Broad diagnostic category (e.g., "Upper respiratory tract infection (URTI)")
+- `messages`: List of alternating user/assistant utterances, each with:
+- `role`: `"user"` or `"assistant"`
+- `content`: Dialogue text
+
+Example:
+```json
+{
+"session_id": 25312,
+"diagn": "Upper respiratory tract infection (URTI)",
+"messages": [
+{"role": "user", "content": "I've had a sore throat and headache for about a day..."},
+{"role": "assistant", "content": "Have you taken any medication before?"},
+...
+{"role": "assistant", "content": "<med_search>"}
+]
+}
+```
+
+> The `<med_search>` token marks the point at which the pharmacist would initiate a medication lookup in the original system. No actual drug recommendations are disclosed.
+
+---
+
+## Citation
+
+If you use this dataset in your research, please cite it as follows:
+
+```bibtex
+@misc
+{realmedconv2025,
+author = {DataJuicer Team, Alibaba Group},
+title = {{RealMedConv}: A Dataset of Real-World Pharmacist-User Dialogues for Online Medication Advice},
+year = {2025},
+note = {Released under CC BY-NC-SA 4.0}
+}
+```
+
+---
+
+## Acknowledgements
+
+We thank the licensed pharmacists and users whose anonymized interactions made this research possible. This work was conducted by DataJuicer Team, Alibaba Group, in alignment with our commitment to responsible AI and data ethics.
+
+---
+
+*This dataset is provided “as is” without warranty of any kind. Users assume all risks associated with its use.*