What the Data for This Category Looks Like
Financial report data for the cultural and entertainment products category comes from public annual reports, quarterly reports, and temporary announcements of listed companies on domestic and overseas securities markets. Updates follow fixed legal financial report cycles, with occasional updates from announcements such as IP license changes and inventory adjustments. Documents include structured financial tables and unstructured business descriptions. Core fields include revenue scale, inventory turnover days, and IP license revenue proportion. Units are based on RMB, with supplementary percentage metrics. Full financial report documents vary widely in length, containing multiple pages of structured reports and business analysis paragraphs.
Constraints Imposed by These Characteristics on Vector Models and Indexing
The mixed structured and unstructured data characteristics of this category require indexes to support fused retrieval of precise matching for structured fields and vector semantic recall. The fixed and occasional update rhythm requires indexes to support incremental updates, avoiding resource consumption from full reconstruction. Multiple fields with different units require vector models to complete field normalization during encoding, eliminating interference from unit differences on similarity calculations. The wide range of document lengths requires a chunking strategy adapted to different text fragment lengths. This avoids too short fragments losing semantic connections, or too long fragments exceeding model context limits.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Cultural and entertainment product financial reports include both short fields (such as single revenue data) and long paragraphs (such as business analysis). This interval balances semantic completeness and retrieval accuracy |
embedding_model | Doubao-embedding | Supports multi-field encoding for financial indicators with different units, matching the data characteristics of this category |
index_refresh_interval | Hourly | Balances update timeliness of temporary announcements and system resource consumption |
recall_top_k | Top 8–12 entries | Financial report analysis requires covering multi-dimensional indicators. A small number of recalls cannot meet full association needs |
structured_field_index | Enabled | This category contains a large number of structured financial fields, which can improve precise matching efficiency |
similarity_threshold | 0.72–0.80 | Filters low-relevance financial report fragments, retaining highly matched analysis content |
The parameter values provided on this page are common starting points 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
- Phenomenon: Search results return irrelevant cultural and entertainment product financial report content. Cause: Structured field indexing is not enabled, only global vector recall is relied on, and the search scope is not narrowed through field filtering.
- Phenomenon: Search requests trigger full document scanning, and response time exceeds expectations. Cause: The document set to be recalled is not limited, and inverted indexing for structured fields is not enabled, causing vector retrieval to cover all data.
- Phenomenon: Index status shows not ready, and retrieval cannot be initiated normally. Cause: Incremental update tasks are not executed according to the configured cycle, or the uploaded financial report documents have format errors leading to parsing failure, and vector encoding is not completed.
How to Confirm Configuration Is Correct
- View the index configuration page, confirm that
structured_field_indexis enabled and associated with the core financial fields in the financial reports. - Initiate a test search, enter a query containing specific financial indicators, and verify whether the search results preferentially return content matching the fields.
- Check the index update log, confirm that the incremental update tasks are executed normally according to the configured cycle, and there are no records of parsing failures or encoding errors.
- Verify that the
embedding_modelconfiguration item matches the currently selected vector model, ensuring that the encoding logic aligns with the category's data characteristics.
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.