Roasted Coffee Retail Product Retrieval Dataset

#product information retrieval #semantic matching #catalog attribute matching #roasted coffee retail #coffee product discovery #intelligent shopping assistants
  • 5000
  • 0.3GB
  • JSON
  • CATL
  • MOBIUSI INCMOBIUSI INC
Updated:2026-10-19

AI Analysis & Value Prop

This dataset contains retail catalog entries for roasted coffee products sold to consumers, paired with natural-language queries. Product information covers attributes such as brand, origin, blend, roast level, bean form, and package size, while each record can include a relevance score, matched attributes, and a rationale. It supports training and evaluation of product search, knowledge retrieval, document retrieval, and query-document matching systems for roasted coffee retail.

Dataset Insights

Sample Examples

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Technical Specifications

FieldTypeDescription
file_namestringFile name
user_querystringA natural-language query submitted by a consumer to retrieve matching coffee products.
product_entryobjectA roasted coffee product offered for sale to consumers, together with its catalog attributes.
relevance_scoreintegerA graded measure of the match between the query and product catalog entry: 0 means irrelevant, 1 means weakly relevant, 2 means relevant, and 3 means highly relevant.
matched_attributesarrayAttribute names identified in the product catalog entry as relevant to the query, such as brand, origin, or roast level.
matching_rationalestringAn explanation of the main reasons the query matches or does not match the product entry.

Compliance Statement

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

Frequently Asked Questions

What does the dataset contain?
It includes roasted coffee retail catalog entries, consumer natural-language queries, relevance scores, matched attributes, and matching rationales. Product attributes may include brand, origin, blend, roast level, bean form, and package size.
How is the relevance score defined?
The score ranges from 0 to 3: 0 means irrelevant, 1 means weakly relevant, 2 means relevant, and 3 means highly relevant. Matched attributes and rationales help explain how a query relates to a product.
What applications is the dataset suited for?
It can be used to train or evaluate product retrieval, knowledge retrieval, and query-document matching models. It is also suitable for developing coffee retail search, query understanding, and search result ranking systems.
How can I obtain the dataset, and what usage restrictions apply?
Check the dataset listing for available access methods, documentation, and samples. The publisher's license determines permitted use, including commercial use; review the license terms and any data restrictions before commercial deployment.

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Cite this Work

@dataset{Mobiusi2026,
  title={Roasted Coffee Retail Product Retrieval Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/0283a4ad2d9b57a091c5806bfff47a16},
  urldate={2026-10-12},
  keywords={roasted coffee dataset, coffee product retrieval, retail product catalog, natural language queries, query-document matching, knowledge retrieval, product search evaluation, coffee retail data},
  version={1.0}
}

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