Roasted Coffee Retail Product Retrieval Dataset
- Records
- 5000
- Size
- 0.3GB
- Format
- JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-05
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.
Overview
Dataset Insights
Preview
Sample Examples
Schema
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. |
Trust
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
FAQ
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_scene_cate_type=4},
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}
}Using this in research? Please cite us.