pandalla/datatager_hospital_service_feedback_analysis

---

license: apache-2.0

If you like our project, please give us a star ⭐

[GitHub | DataTager Home]

Hospital Service Feedback Analysis

Prompt for Training

When training your model with this dataset, prepend the following prompt to each input instance:

根据提供的酒店评论文本，自动识别出评论中的关键特征，并对每一个关键特征进行100分制的评分。同时，需要为每个关键特征提供一段解释，说明为何给出该评分。

Description

AnyTaskTune is a publication by the DataTager team. We advocate for rapid training of large models suitable for specific business scenarios through task-specific fine-tuning. We have open-sourced several datasets across various domains such as legal, medical, education, and HR, and this dataset is one of them.

This dataset, titled "Hospital Service Feedback Analysis " is part of an initiative by the DataTager team under the AnyTaskTune publication, categorized under AnyTaskTune-ConsumerService. It focuses on transforming raw and emotionally charged hospitality feedback into structured ratings and assessments. This transformation aims to provide clear insights from customer feedback, thereby enhancing service delivery and customer satisfaction in the hospitality industry.

Usage

This dataset is invaluable for training AI systems aimed at hospitality service evaluation and customer relationship management. By converting unstructured guest feedback into structured evaluations, these AI models can help automate the assessment of customer satisfaction and service quality. This not only aids in identifying areas needing improvement but also helps in recognizing strengths. Additionally, the dataset can be employed in training programs for hospitality management students, teaching them how to analyze customer feedback effectively and implement service improvements based on real-world data.

Citation

Please cite this dataset in your work as follows:

@misc{ Extract Medical Information Dataset,
  author = {DataTager},
  title = {Extract Medical Information Dataset},
  year = {2024},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\\url{https://github.com/PandaVT/DataTager}}
}