Small Appliance Product Discovery and Retrieval Dataset

#product information retrieval #semantic matching #evidence retrieval #small appliance retail #product discovery #intelligent shopping assistants

5000
0.2GB
JSON
CATL
MOBIUSI INC

Updated:2026-10-19

AI Analysis & Value Prop

This dataset pairs consumer queries about small appliance purchases, including intended use, capacity, features, dimensions, and budget, with retail product pages, product details, and query–product relevance labels. It also provides structured query requirements and product attributes, supporting key steps from understanding shopper needs and extracting product information to judging relevance. Typical uses include training and evaluating document retrieval and query–document matching models, as well as retail knowledge search, product search, semantic retrieval, and retrieval system evaluation.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
is_relevant	boolean	A binary relevance judgment derived from the relevance label.
product_brand	string	The brand name extracted from the product page.
product_price	number	The product price extracted from the product page and normalized as a numeric value.
product_title	string	The product name or page title extracted from the product page.
consumer_query	string	The original small appliance purchase request, expressed in terms such as intended use, capacity, features, dimensions, or budget.
relevance_label	integer	The query-to-product relevance grade provided by the dataset or assigned by annotators; interpret its numeric value according to the dataset annotation guidelines.
normalized_query	string	The consumer query after cleaning and normalization, with its original intent preserved.
product_category	string	The small appliance category or subcategory identified from the product page.
product_currency	string	The currency code or currency name associated with the product price.
product_depth_cm	number	The product depth extracted from the page specifications and converted to centimeters.
product_features	array	A list of functions, specifications, selling points, or other product features extracted from the page.
product_width_cm	number	The product width extracted from the page specifications and converted to centimeters.
query_max_budget	number	The maximum budget amount parsed from the query.
matching_evidence	array	A list of text snippets from the product page that support the relevance judgment.
product_height_cm	number	The product height extracted from the page specifications and converted to centimeters.
product_page_html	string	Raw HTML from a small appliance retail page containing product details, specifications, prices, and related information.
product_page_text	string	Product detail text extracted from the original page and cleaned for use.
query_intended_use	string	The intended use or usage scenario identified from the consumer query.
query_max_depth_cm	number	The maximum depth requirement parsed from the query and converted to centimeters.
query_max_width_cm	number	The maximum width requirement parsed from the query and converted to centimeters.
product_description	string	A description organized from the product page, covering its intended use, features, and suitable scenarios.
query_max_height_cm	number	The maximum height requirement parsed from the query and converted to centimeters.
query_budget_currency	string	The currency code or currency name used for the budget in the query.
product_capacity_liters	number	The product capacity extracted from the page specifications and converted to liters.
query_required_functions	array	A list of target functions or performance requirements identified in the query.
matched_query_constraints	array	A list of consumer requirements that match information found in the product details.
unmatched_query_constraints	array	A list of consumer requirements that the product does not meet or that cannot be verified from the page.
query_required_capacity_liters	number	The capacity requirement parsed from the query and converted to liters.

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?: The dataset centers on small appliance shopping queries and retail product pages. It includes raw queries, product page HTML and text, product information such as titles and brands, and relevance labels. Structured fields also cover intended use, capacity, budget, features, dimensions, product attributes, matched and unmatched constraints, and supporting evidence snippets.

How can the data support retrieval training and evaluation?: Queries paired with product pages and relevance labels can form query–product document matching examples for training or evaluating retrieval models. Normalized queries, structured requirement attributes, matched and unmatched constraints, and text evidence can also help analyze retrieval results and improve ranking. Interpret relevance grades according to the annotation guidelines supplied with the dataset.

How can I verify dataset size and field quality?: The available information does not specify the number of records, the time span of page coverage, or quality assurance metrics, so these should not be assumed. The fields include raw pages alongside extracted and normalized information; before use, check the dataset version, field definitions, missing values, and annotation guidelines.

How can I obtain the data, and what licensing rules apply?: Refer to the dataset release page or provider for download or delivery details; no license type is specified in the available information. Before use, confirm the permitted scope, any commercial-use restrictions, copyright and redistribution requirements for webpage content, and applicable data protection and website terms.

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Cite this Work

@dataset{Mobiusi2026,
  title={Small Appliance Product Discovery and Retrieval Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/3d6f213e62f76035f3d126e10cc879f4?dataset_scene_cate_type=4},
  urldate={2026-10-10},
  keywords={small appliance retrieval dataset, product discovery data, product search training data, query document matching, retail knowledge retrieval, product relevance labels, small appliance product data, semantic retrieval evaluation},
  version={1.0}
}

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