What the data for this category looks like
Core sources of footwear investment research data include brand product specification documents, footwear technology and trend reports released by industry associations, footwear sales monitoring data from e-commerce platforms, and footwear structural patent documents from patent databases. Update rhythms vary across sources: industry reports are updated quarterly, product specification documents are updated dynamically with new product launches, sales data is updated weekly, and patent documents are updated in real time. Document structures fall into three categories: Product documents include shoe type, material type, size chart, production lead time, and retail guide price. Industry reports include category structure and consumer group preferences. Patent documents include structural details, application date, and authorization status. Field units include millimeters (mm), EU sizes, yuan, and others. Some documents contain multi-unit size comparison information.
What constraints do these characteristics impose on knowledge base retrieval and recall?
Heterogeneous documents from multiple sources require different parsing rules. Structured product tables and unstructured industry reports need separate parsing template configurations. Data with different update rhythms requires differentiated synchronization strategies. Weekly sales data needs high-frequency incremental synchronization, while quarterly reports need regular full synchronization. Otherwise, outdated information will appear in recall results. Multi-unit field information needs unified mapping rules. This avoids missing documents corresponding to EU sizes, UK sizes, etc., when users search for "size 42 shoes". Professional jargon such as "last shape" and "outsole wear resistance coefficient" needs a dedicated terminology library. Otherwise, semantic deviation will occur during retrieval. A large number of SKUs will lead to redundant recall results. Adjust the number of recalled entries and thresholds to control context length.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Recall Count | Top 10 entries | Footwear has a large number of SKUs. Too many recalled entries per round increases context processing load. 10 entries can cover core relevant content |
Similarity Threshold | 0.72–0.78 | Footwear has many similar expressions, such as "full-grain leather" and "top-grain leather". A threshold that is too low introduces irrelevant content. A threshold that is too high misses relevant documents |
Chunk Length | 800–1200 characters | Footwear product documents contain long paragraphs such as size charts and material descriptions. Chunks that are too long lose context association. Chunks that are too short destroy the integrity of professional terms |
Incremental Sync Cycle | Weekly | Footwear sales data is updated weekly. Incremental synchronization ensures the timeliness of retrieval content |
Terminology Dictionary Configuration | Load a dedicated footwear investment research terminology library | Footwear has a large number of specialized terms, which improves retrieval accuracy |
Reranked Return Count | Top 3 entries | Core investment research content needs priority display. The top 3 entries after reranking focus on the most relevant professional information |
The parameter values provided on this page are all conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three common configuration mistakes
- Symptom: The latest weekly sales data does not appear in retrieval results. Cause: The incremental sync cycle was not configured, and only full synchronization was performed. This results in a mismatch between update frequency and data release rhythm.
- Symptom: Retrieval results contain a large number of irrelevant general textile fabric documents, without focusing on footwear content. Cause: The dedicated footwear terminology dictionary was not loaded, and the similarity threshold was set too low. This makes it impossible to distinguish professional expressions between footwear and general textile categories.
- Symptom: Responses only cite complete document entries, without displaying specific paragraph fragments. Cause: The document paragraph-level recall configuration was not enabled, and only overall document recall was performed. This makes it impossible to extract accurate citation fragments. This corresponds to the scenario where paragraph-level citation extraction was not enabled in version 3.9.2.
How to confirm the configuration is correct
- Perform a retrieval targeting footwear-specific terminology, and verify that returned results prioritize footwear-related documents, and general textile category content is not prioritized.
- Check sync task logs to confirm that incremental sync tasks run according to the preset cycle, and only sync updated documents.
- Generate a test response, and verify that cited fragments are specific paragraphs within the document, and not complete document entries.
- Adjust the similarity threshold, observe changes in the relevance of retrieval results, and confirm that the threshold meets the recall requirements of the current business.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.