Designer and Premium Fashion Product Retrieval Dataset

#semantic retrieval #natural-language query matching #product catalog retrieval #designer fashion e-commerce #premium apparel search #luxury product discovery

5000
0.4GB
JSON
CATL
MOBIUSI INC

Updated:2026-10-25

AI Analysis & Value Prop

Designed for designer and premium fashion retail, this dataset pairs product catalog records with natural-language product queries and query-product relevance annotations. Search documents bring together product names, designers, categories, descriptions, and available attributes to support consistent product indexing. The data can be used to train and evaluate product-query matching, relevance ranking, and catalog retrieval systems.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
user_query	string	The original natural-language request used to search for a matching fashion product.
relevance_grade	integer	The original relevance annotation for this query-product pair, using the dataset's grading convention.
search_document_text	string	A derived text representation that combines the product's catalog name, designer, category, description, and available attributes for retrieval indexing.
product_catalog_record	object	The original structured catalog entry for the designer fashion product being evaluated.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What does the dataset contain?: Each record includes product catalog information, a natural-language user query, a relevance grade for the query-product pair, and a text representation prepared for search indexing. The representation can combine the product name, designer, category, description, and available attributes.

How should the relevance grades be used?: Relevance grades indicate how well a product matches its query. Refer to the dataset's annotation guidelines for the meaning of each grade. The labels can support relevance model training, ranking systems, and retrieval benchmarks.

Which applications and training tasks does it support?: It is suitable for designer and fashion catalog search, natural-language product discovery, and virtual shopping assistance. Supported tasks include document retrieval, query-product matching, relevance ranking, and retrieval evaluation.

How can I access the data, and what are the licensing terms?: Check the dataset product page for access options, license scope, and usage restrictions. Before commercial deployment or redistribution, verify the applicable license and permissions for both catalog content and annotations.

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Cite this Work

@dataset{Mobiusi2026,
  title={Designer and Premium Fashion Product Retrieval Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/3341358560666b53bf0b3f35f2eb1d93},
  urldate={2026-10-20},
  keywords={designer fashion dataset,premium fashion product retrieval,product catalog search data,natural language product queries,query product matching data,fashion e-commerce search,product relevance labels,document retrieval evaluation},
  version={1.0}
}

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