Create dataset (UIT-ViOCD)

- uid: (UIT-ViOCD)
- type: processed
- description:
- name: Vietnamese Complaint Detection on E-Commerce Websites
- description: Customer product reviews play a role in improving the quality of products and services for organizations or brands. Complaining is an attitude that expresses dissatisfaction with an event or a product not meeting customer expectations. In this paper, we build a Vietnamese dataset (UIT-ViOCD), including 5,485 human-annotated reviews on four categories about product reviews on e-commerce sites. After the data collection phase, we proceed to the annotation task and achieve Am = 87% by Fleiss' Kappa. Then, we present an extensive methodology for the research purposes and achieve 92.16% by F1-score for identifying complaints. With the results, in the future, we want to build a system for open-domain complaint detection in E-commerce websites.
- homepage: https://arxiv.org/pdf/2104.11969.pdf
- validated: True
- languages:
- language_names:
- Vietnamese
- language_comments:
- language_locations:
- South-eastern Asia
- Vietnam
- validated: False
- custodian:
- name: Ms. Nhung
- in_catalogue:
- type: A university or research institution
- location: Vietnam
- contact_name: Ms. Nhung
- contact_email: 18521218@gm.uit.edu.vn
- contact_submitter: False
- additional:
- validated: False
- availability:
- procurement:
- for_download: Yes - after signing a user agreement
- download_url: 18521218@gm.uit.edu.vn
- download_email:
- licensing:
- has_licenses: Unclear
- license_text:
- license_properties:
- license_list:
- pii:
- has_pii: Unclear
- generic_pii_likely:
- generic_pii_list:
- numeric_pii_likely:
- numeric_pii_list:
- sensitive_pii_likely:
- sensitive_pii_list:
- no_pii_justification_class: general knowledge not written by or referring to private persons
- no_pii_justification_text:
- validated: False
- processed_from_primary:
- from_primary: Taken from primary source
- primary_availability: Yes - their documentation/homepage/description is available
- primary_license: Unclear / I don't know
- primary_types:
- validated: False
- from_primary_entries:
- media:
- category:
- text
- text_format:
- audiovisual_format:
- image_format:
- database_format:
- text_is_transcribed: No
- instance_type:
- instance_count:
- instance_size:
- validated: False
- fname: (UIT-ViOCD).json

首先定位现有的数据集记录和仓库的验证指南，然后将它们的结构与请求的 (UIT-ViOCD).json 条目进行比较。使用链接的论文和 issue 中的元数据创建该记录，并确认仓库的数据集验证接受它。

由索引模型根据 Issue 内容生成。