Data Characteristics
Regulatory search data in the biomedical field originates from internal corporate regulations, Standard Operating Procedures (SOPs), Quality Management System documents, compliance guidelines, and project management specifications. These documents typically have low update frequencies, with quarterly or annual revisions. However, urgent updates occur when policy changes or internal process optimizations are implemented. Document structures are predominantly hierarchical and clearly itemized, in plain text or PDF formats containing tables and diagrams. Common fields include version number, effective date, revision history, scope, and responsible department. Some regulations include specific chemical names, equipment models, and experimental method numbers. These fields do not have uniform units; instead, they use specific naming conventions based on their professional attributes.
Constraints Imposed by These Characteristics on Knowledge Base Retrieval and Recall
The low update frequency of regulatory documents means that a large volume of data needs to be imported during the initial knowledge base construction. Subsequent incremental update pressure is minimal, but version management is critical. Clear distinction between retention of old versions and activation of new versions is necessary. Complex document structures, including numerous specialized terms and cross-references, demand robust segmentation strategies to ensure semantic completeness. The presence of specialized terms and numbers requires the retrieval model to have strong exact matching capabilities to avoid semantic generalization leading to incorrect recalls. User queries often involve regulations within specific departments, processes, or timeframes, necessitating metadata-based filtering capabilities to narrow the search scope and improve relevance. Insufficient understanding of chart content can lead to loss of critical information, affecting retrieval accuracy.
Configuration Settings
| Configuration Item | Recommended Value | Rationale for Recommendation |
|---|---|---|
Chunk size | 800–1200 characters | Regulatory document paragraphs are long and contain complete semantics; this length prevents information loss due to segmentation. |
Chunk Overlap Length | 100–200 characters | Ensures contextual continuity between adjacent paragraphs and handles cross-paragraph semantic dependencies. |
Recall count | 10–15 entries | Balances coverage while controlling the number of returned results, reducing subsequent processing burden. |
Similarity threshold | 0.75–0.85 | Regulatory retrieval demands high accuracy; a high threshold filters out irrelevant results, preventing misinformation. |
Rerank result count | 5 entries | Precisely filters the most relevant few results, enhancing user experience. |
MAX_FILE_SIZE_MB | 50 MB | Considering that regulatory documents may include charts, file sizes can exceed those of ordinary text files. |
Common Pitfalls
- Query results contain numerous outdated or abolished regulatory entries. This occurs when the knowledge base fails to effectively distinguish document versions or effective statuses during document import or update.
- The system fails to recall corresponding regulations after a user enters a specific regulation number or process name. This manifests as empty or irrelevant results. This occurs because key metadata was not included as a searchable field during the knowledge base indexing process.
- After importing into the knowledge base, executing a query results in an
IndexNotFoundExceptionor similar error, leading to no query results. This occurs when knowledge base document import does not trigger or successfully complete index rebuilding.
How to Verify Configuration
- For typical query statements, verify that recall results include the expected relevant regulatory documents and accurate paragraphs, and check if their versions are the latest effective ones.
- Select regulations from multiple departments and different business processes. Use precise queries for their titles or numbers to confirm accurate recall and evaluate the relevance ranking of the recall results.
- Simulate user queries for recently revised regulations to confirm that the knowledge base can promptly reflect updated content and differentiate between new and old versions.
- Check the knowledge base backend management interface to confirm that all imported regulatory documents have been successfully indexed and show normal status.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-21.