What the Data for This Category Looks Like
Decoration and renovation marketing content data for the finance industry mainly comes from institutional outlet renovation plans, soft furnishings materials for wealth management studios, workplace renovation copy and quotation templates. The update rhythm fluctuates with outlet adjustments, event venue renovations, and brand image upgrades, with no fixed cycle. Document types cover structured Excel quotation sheets, unstructured plan texts, short video scripts, and on-site feedback documents. Fields include decoration style, internal floor area (unit: ㎡), budget range (unit: ten thousand yuan), construction period (unit: days), material size (unit: mm), and others. The length of individual documents varies widely, ranging from hundreds of words of event scripts to tens of thousands of words of complete outlet renovation plans.
What Constraints These Characteristics Impose on Vector Models and Indexing
The multi-type data characteristics of finance industry decoration and renovation marketing content impose multiple constraints on the vector model and indexing step. Structured numerical fields require separate vectorization. Without this step, key retrieval needs such as budget and area cannot be accurately matched. The non-fixed update rhythm requires support for batch indexing and scheduled retraining to avoid the inefficiency of manual single-file processing. The large difference in document length requires flexible adjustment of segmentation parameters to avoid semantic fragmentation or overly short segments. Numerical fields with units require unified normalization. Without this step, vector deviations occur for similar content with different units. Frequently reused brand template content easily produces duplicate fragments, so deduplication logic needs to be configured.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_EXCEL_FIELD_ENABLE | Enabled, enable vectorization of numerical fields | Decoration and renovation marketing content includes structured numerical fields such as budget and internal floor area. Converting these fields to vectors improves accurate recall |
CHUNK_MAX_SIZE | 800–1200 characters | The single-segment semantics of renovation plan texts need to be complete. This range adapts to the input length limits of most open-source vector models and avoids semantic fragmentation |
BATCH_INDEX_MAX_FILES | 50 files per batch | The decoration and renovation case library has a large number of files. Batch processing reduces the probability of indexing timeouts and ensures process stability |
SIMILARITY_SCORE_THRESHOLD | 0.72–0.78 | There are obvious differences in decoration content styles and budget ranges. This threshold filters irrelevant results while covering valid matching content |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Large panoramic case documents have large file sizes. Raising the single-file upper limit supports complete material uploads |
RECALL_TOP_K | Top 8 results | Marketing content recall needs to cover multiple styles and budget options. This quantity balances recall range and retrieval efficiency |
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 specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: Batch vector retraining only supports single-file parameter adjustments, and batch triggering is not available. Cause: The preset parameter binding function for batch indexing is not enabled, and only the single-file manual configuration mode is activated.
- Phenomenon: A single document is initially split into 8 segments, and later changes to 13 segments with duplicate fragments. Cause: No reasonable interval is configured for the
CHUNK_OVERLAPparameter, leading to duplicate segment overlap counting, or duplicate header and footer content in the document is not filtered during parsing. - Phenomenon: Index results do not meet expectations after vectorizing Excel files, and some budget fields are not recalled. Cause: The
PARSE_EXCEL_FIELD_ENABLEconfiguration is not enabled, and only text content is vectorized, without including structured numerical fields.
How to Confirm Configurations Are Correctly Set
- Upload an Excel quotation sheet containing budget and area fields, and confirm that the parsed vector data includes vectorized content of structured fields.
- Upload a complete renovation plan document, and check that the length of split segments meets the configured range, with no obvious semantic fragmentation.
- Run a batch indexing task, and confirm that multiple files can be processed simultaneously, with no mandatory restrictions on single-file separate parameter configuration.
- Launch a retrieval test, enter keywords corresponding to the marketing scenario, and check whether the coverage of recall results meets business needs.
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.