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 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

Field	Type	Description
file_name	string	File name
user_query	string	A natural-language query submitted by a consumer to retrieve matching coffee products.
product_entry	object	A roasted coffee product offered for sale to consumers, together with its catalog attributes.
relevance_score	integer	A 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_attributes	array	Attribute names identified in the product catalog entry as relevant to the query, such as brand, origin, or roast level.
matching_rationale	string	An explanation of the main reasons the query matches or does not match the product entry.

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?: 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?dataset_task_cate_id=10},
  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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