bigscience-workshop / bigscience-workshop/data_tooling
Create dataset (UIT-ViOCD)
- Dominant language
- HTML
- Stars
- 91
- Forks
- 47
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Description
- 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
Contributor guide
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Research direction
Start by locating existing dataset records and the repository’s validation guidance, then compare their structure with the requested (UIT-ViOCD).json entry. Use the linked paper and the metadata in the issue to create the record, and confirm that the repository’s dataset validation accepts it.
Written by the indexing model from the issue text.
Assessment
- Domain
- data
- Issue type
- Feature
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 42/100