What the Data for This Category Looks Like
Industrial park marketing content sources include official investment promotion materials of park operators, local industrial policy public documents, settled enterprise activity ledgers, park supporting facility description documents, and quarterly marketing activity plans. Update rhythm: industrial policies are updated quarterly to annually per local government requirements, settled enterprise information is updated monthly alongside investment promotion progress, park activity content is temporarily updated per quarterly marketing plans, and site parameters and industrial positioning remain long-term stable. Document structure includes structured fixed fields and unstructured long text. Structured fields include park unique identifier, industrial track classification, rentable area, settled enterprise industry classification, policy subsidy amount, and official contact information. Unstructured sections include park planning interpretation, detailed success cases of settled enterprises, and event site descriptions.
What Constraints Do These Characteristics Impose on Vector Models and Indexing?
The multi-field mixed structure of industrial park marketing content requires the vector index system to support joint encoding of structured fields and unstructured text. Performing vector encoding only on the full text will lose structured parameter information. The varying update frequencies of different content require the index system to support incremental update mechanisms, triggering indexing separately for frequently changed settled enterprise information and activity content without fully rebuilding the entire index library. The documents contain standardized numerical fields, so the vector model must support vectorization conversion of numerical fields to ensure information such as area and subsidy amount is correctly encoded. There are numerous repeated expressions of general policies in the marketing content, so the index must support keyword-based pre-filtering to reduce redundant vector storage usage.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
vector_model | Select a model adapted for Chinese long text and numerical fields, such as bge-large-zh-v1.5 | Industrial park marketing content includes long-text policy interpretations and structured parameters; the encoding effect of this model meets scene requirements |
chunk_size | 800–1200 characters | Industrial park documents contain both long-text policy descriptions and short-field parameters; this range balances semantic completeness and indexing granularity after segmentation |
index_refresh_interval | 3600 seconds | Settled enterprise information and activity content see minor updates daily; hourly incremental refresh balances real-time performance and resource usage |
recall_top_k | Top 10–15 results | Retrieval of marketing content needs to cover multi-dimensional park resources; this recall volume ensures matching of different types of investment promotion information |
similarity_threshold | 0.72–0.80 | Filter low-similarity irrelevant text and retain differentiated investment promotion content for different parks |
structured_field_encoding | Enabled | Industrial park documents contain standardized numerical fields; enabling this allows separate encoding of fields such as area and subsidy amount and inclusion in the joint index |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require case-by-case analysis; it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Phenomenon: No optional options appear in the interface vector model dropdown menu, making index configuration impossible. Cause: The runtime environment for the corresponding vector model has not been deployed in the system, or the correct model identifier has not been filled in the configuration items.
- Phenomenon: A large number of irrelevant general policy texts are mixed in the retrieval results, and the number of recalled entries far exceeds expectations. Cause: The
similarity_thresholdparameter is not set, or the threshold is set too low, causing low-similarity texts to be incorrectly recalled. - Phenomenon: Newly released park activity content does not appear in retrieval results in a timely manner. Cause: The
index_refresh_intervalis set to an overly long time period that does not match the update rhythm of park activity content.
How to Confirm Proper Configuration
- Upload a park investment promotion brochure document, check the parsed segmentation results, and confirm that the segmentation length matches the preset
chunk_sizerange. - Manually trigger an incremental index, check whether the
index_refresh_successstatus code appears in the system log, and confirm that the index update process is working normally. - Enter the retrieval term "biomedical park rentable area", check whether the retrieval results include information corresponding to the structured fields, and confirm that the joint index has taken effect.
- Adjust the
similarity_thresholdparameter, retrieve the same keyword again, observe the change in the number of recalled results, and confirm that the threshold configuration has the expected impact on retrieval results.
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.