What the Data for This Category Looks Like
Satellite communications investment research data sources include public orbital parameter databases, ground station operation logs, communication link test reports, industry standard documents, and third-party investment research reports. Data update rhythms fall into three categories: Static parameters such as orbital inclination and carrier frequency are updated quarterly. Dynamic parameters such as link bandwidth and signal coverage are pushed hourly or in real time. Industry research reports are updated per their release cycles.
Document structures include structured parameter tables, unstructured operation logs and test records. Fields cover standardized metrics: orbital altitude (unit: km), carrier frequency (unit: MHz), throughput (unit: Mbps), signal delay (unit: ms), plus a small amount of qualitative descriptive content without units.
What Constraints These Characteristics Impose on Vector Models and Indexing
The standardized metric attributes of static parameters require vector models to accurately match numerical and unit-related semantics, to avoid semantic deviations caused by mixed unit usage. The high-frequency update characteristics of dynamic data require indexes to support incremental updates and scheduled full refreshes, to reduce resource overhead of full reconstruction. The mixed document structure requires chunking strategies to adapt to differences between long and short texts, to avoid over-splitting short parameters or semantic fragmentation in long logs. The coexistence of unitless qualitative descriptions and structured parameters requires indexes to support both semantic vector retrieval and keyword matching, to cover different types of investment research query needs.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk Length | 800–1200 characters | Adapts to mixed document structures, balances semantic integrity of structured parameters and contextual coherence of long logs |
Number of Retrieved Results | Top 15–20 results | Covers multi-source link test reports and operation logs, meets comprehensive data retrieval needs for investment research scenarios |
Similarity Threshold | 0.85–0.90 | Meets high-precision matching requirements for standardized metric parameters, filters irrelevant content with low matching degrees |
Incremental Index Trigger Threshold | Triggered when newly added data accounts for 5% of total index volume | Adapts to high-frequency update characteristics of dynamic data, balances update overhead and data freshness |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Meets parsing duration requirements for large operation log files, avoids timeout interruptions |
Number of Reranked Returned Results | Top 5–8 results | Focuses on core investment research data, reduces interference of non-essential information on decision-making |
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 testing should be conducted on samples relevant to the deployment before finalizing values.
Three Common Misconfigurations
- Phenomenon: When performing batch retraining of the vector model, only single-file upload is supported, and global retraining tasks cannot be triggered. Cause: By default, only the single-file incremental training switch is enabled, and the global batch training configuration item is not activated.
- Phenomenon: After a document is uploaded, it displays 8 segments, and after a period of time becomes 13 segments with duplicate fragments. Cause: Document deduplication preprocessing is not enabled, and the chunk length is set too short, causing the same content to be split and included multiple times.
- Phenomenon: After upgrading from 4.9.0 to 4.9.3, previously queryable document content can no longer be retrieved. Cause: The new version's vector model embedding dimension has changed, the original index was not automatically rebuilt, and the index refresh logic after version upgrade was not configured.
How to Verify Proper Configuration
- Upload a mixed document containing an orbital parameter table and an operation log of more than 1000 words, then check that the number of parsed segments matches the expected range defined in the configuration.
- Submit an incremental index task, then check that the processing status of newly added data in the system log is successful, and there are no duplicate segment marker records.
- Initiate a query containing satellite carrier frequency parameters, verify that the similarity scores of the retrieved results fall within the configured threshold range, and the reranked results follow the logic of prioritizing core data.
- Trigger a global batch training task, wait for the task to complete, then check the update status of embedding vectors of all documents in the vector database, with no failed entries.
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.