Wearable Activity Scenario and Product Matching Dataset

#Query-Document Matching #Product Relevance Ranking #Retail Semantic Retrieval #Match Evaluation #Wearable Shopping #Sports Retail #Product Search and Recommendations #Health Product Discovery

8800
0.5GB
JSON
CATL
MOBIUSI INC

Updated:2026-11-03

AI Analysis & Value Prop

This dataset pairs natural-language customer needs with wearable product catalog documents across running, swimming, hiking, commuting, travel, and everyday health management scenarios. Its fields cover scenario category, activity goal, usage environment, required features, product capabilities, match labels and scores, supporting evidence, and reasons for mismatches. These structured examples support training and evaluating query-to-product matching models for real-world retail, as well as product retrieval, recommendation ranking, and match analysis.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
query_text	string	A natural-language request from a customer for activities such as running, swimming, hiking, commuting, travel, or everyday health management.
match_label	string	A label indicating the overall degree of match between the product catalog document and the customer request.
match_score	number	A normalized score for the degree to which the product meets the request, ranging from 0 to 1.
activity_goal	string	The main activity goal extracted from the query, such as workout tracking, health monitoring, route navigation, or everyday reminders.
match_evidence	string	Key evidence in the product catalog document that supports or corresponds to the customer requirements.
mismatch_reasons	array	Specific missing features, limitations, or conflicts when a product does not fully meet the customer requirements.
required_features	array	A list of features, performance attributes, or usage requirements extracted from the customer request.
scenario_category	string	The primary activity or use scenario inferred from the customer request.
usage_environment	string	The usage environment inferred from the request, such as an indoor pool, outdoor mountains, city streets, or a daily office setting.
product_capabilities	array	A list of product features or attributes extracted from the catalog document that can meet the customer's needs.
product_catalog_document	string	The wearable product catalog document to be matched, including product name, features, specifications, and suitable use cases.

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 natural-language customer needs, wearable product catalog documents, and fields for scenario category, activity goal, usage environment, required features, product capabilities, match labels and scores, supporting evidence, and mismatch reasons.

Which models and tasks can it support?: The data supports query-to-product document matching, semantic product retrieval, relevance ranking, and retail recommendations. It can also be used to evaluate whether products meet customer needs in specific activity scenarios.

How are match labels and scores used?: The match label represents the overall degree of fit, while the normalized match score ranges from 0 to 1. Evidence and mismatch reasons help analyze model decisions and support more detailed error evaluation.

How can I access the data and verify its license?: Check the dataset page or the provider's designated channel for available formats, access instructions, and license terms. Confirm the applicable permissions before use, especially for commercial deployment or redistribution.

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Cite this Work

@dataset{Mobiusi2026,
  title={Wearable Activity Scenario and Product Matching Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/bf9d9771b48c2a404d05a8ade1937eff?dataset_task_cate_id=1},
  urldate={2026-10-28},
  keywords={wearable dataset,product matching data,query document matching,smartwatch retrieval,sports scenario recommendations,retail semantic search,product relevance ranking,health device shopping},
  version={1.0}
}

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