What the Data for This Category Looks Like
Air pollution control research report data mainly comes from public documents of environmental industry research institutions, local ecological environment departments, completion documents of air pollution control projects, and statistical materials of industry associations. There are three update schedules: quarterly full-industry research reports, monthly documents on regional pollution monitoring and governance progress, and special temporary research reports generated after sudden pollution incidents. Document structures typically include abstracts, policy clauses, technical parameters, project cases, and compliance standards. Fields include report number, issuing organization, release date, coverage area, core pollutant indicators (units: mg/m³, tons/year), and technical solution details.
Constraints Imposed on Knowledge Base Retrieval and Recall
Dispersed data sources lead to significant differences in the authority and timeliness of recall results. Configure targeted weight rules to distinguish the priority of documents from different sources. Uneven update frequencies exist, including both fixed-cycle quarterly reports and temporarily triggered special documents. Support both scheduled incremental updates and event-triggered synchronization to avoid recalling outdated content. Documents contain technical parameters and policy clauses with specific units. Retain field metadata during retrieval to enable precise matching, preventing invalid recalls caused by unit mismatches. Long documents account for a high proportion. Adjust segmentation granularity to match the integrity of professional expressions, avoiding damage to technical logical connections.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Recall count | Top 10–15 entries | Each air pollution control research report has relatively long content; too many recalled entries will exceed the context window, while too few will fail to cover core technical and policy information |
Similarity threshold | 0.72–0.85 | Need to distinguish between professional terminology and general expressions, avoid irrelevant content being matched, while covering professional queries in specific scenarios |
Chunk size | 800–1200 characters | Air pollution control research reports include technical parameters and policy clauses; overly long segments will lose semantic connections, while overly short segments will damage the integrity of professional expressions |
Incremental Update Cycle | Weekly + event trigger | Quarterly research reports are updated on a fixed cycle, and sudden special reports are synchronized via event triggers, matching the data update schedule |
Field Weight Configuration | Release date weight 1.2, technical parameter field weight 1.5 | Prioritize recalling the latest documents that include core technical parameters, aligning with scenario-based retrieval needs |
Rerank result count | Top 5–8 entries | Perform secondary ranking on initial recall results to filter out content with unit mismatches or outdated policies, improving result accuracy |
This page provides parameter values as common starting points for defining configurations. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Semantic search returns completely unrelated documents. The cause is failure to configure field weights for air pollution control-specific professional units such as mg/m³, leading to incorrect elevation of semantic matching scores between general expressions and professional content.
- Knowledge base metadata cannot be synchronized to MySQL databases. The cause is failure to configure association mapping rules between the knowledge base and MySQL data sources, making field matching and writing impossible.
- PGVector knowledge base fails to perform normal retrieval after migration. The cause is failure to convert field metadata unique to air pollution control research reports such as regional codes and pollutant units, leading to the target database being unable to recognize the original index structure.
How to Verify Correct Configuration
- Launch a professional query that includes specific pollutant units or regional codes, verify whether returned results include corresponding fields, and confirm field weight configuration is effective.
- Trigger an incremental update task, review data source synchronization logs, and confirm update cycles and event trigger rules match actual data update schedules.
- Test long document segmented retrieval, review returned context for complete technical parameter expressions, and confirm segmentation length configuration is reasonable.
- Compare initial recall results with reranked results, confirm reranking logic filters irrelevant or outdated content, and improves result accuracy.
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.