What the data for this category looks like
Semiconductor research report data comes from leading securities research institutions, third-party semiconductor industry consulting firms, and publicly available materials from industry exhibitions. Update cycles include regular and emergency scenarios: industry dynamic reports are updated weekly, in-depth analysis reports are updated quarterly, and temporary reports are added when new products enter mass production or industrial policies are released. Document structures include abstracts, industry macro analysis, segmented track data, corporate revenue breakdowns, risk warnings, and other sections. Main text often includes structured data tables, with fields including publishing institution name, release timestamp, covered product type, core business indicator value, and corresponding unit.
What constraints these characteristics impose on vector models and indexing
Semiconductor research reports have dense technical terminology and structured business indicators. This requires vector models to support semantic embedding for the electronic semiconductor field; general models cannot accurately capture connections between professional concepts. Research report updates follow regular and emergency rhythms, so indexes must support incremental updates to avoid excessive time spent on full reconstruction. Structured data tables in documents require association between fields and units, so indexes must support mixed retrieval logic for text and numerical values. Research report content varies significantly across different segmented tracks, so index shards should be divided by track to improve recall accuracy.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
embedding_model | bge-large-zh-v1.5 (or domain-fine-tuned embedding models) | Adapts to Chinese professional text, delivering more stable semantic embedding for semiconductor terminology and industrial indicators |
chunk_size | 800–1200 characters | Semiconductor research reports contain long sentences and structured tables. Excessively long segments split professional logic, while excessively short segments lose contextual connections |
index_shard_count | 3–5 shards | Divide shards by segmented tracks such as wafer manufacturing, memory chips, and design services to improve retrieval concurrency and recall accuracy |
incremental_index_enable | Enabled | Adapts to the rhythm of regular and emergency research report updates, reducing time spent on full index reconstruction |
numeric_field_index | Enabled, associated with \wafercapacity\, \flashprice\ fields | Research reports contain structured business indicators, requiring mixed retrieval logic for text and numerical values |
similarity_threshold | 0.72–0.85 | Balances coverage and accuracy of recall results, avoiding irrelevant non-semiconductor industry research reports |
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 settings.
Three common mistakes
- Symptom: Index reconstruction tasks run continuously for more than 24 hours, and the backend log returns the
ETIMEDOUTerror. Cause: Incremental indexing is not enabled, and full index reconstruction is performed for each research report update, exceeding system processing thresholds. - Symptom: The batch add index API call returns a
400 Bad Requesterror, with the return fieldmissing_required_param. Cause: Theindex_shard_idfield is not configured in the request parameters, and index shard ownership is not specified. - Symptom: A large amount of non-semiconductor track research report content is included in retrieval results, and recall accuracy is insufficient. Cause: An independent index is created for each research report, and a unified collection index is not used, resulting in inability to batch match relevant track research report collections during retrieval.
How to confirm the configuration is complete
- Check the embedding model configuration item to confirm that a professional domain-adapted embedding model has been selected.
- Submit a new research report for update, check the index update log to confirm that only the incremental synchronization process is executed.
- Call the batch add index API, pass request parameters containing
index_shard_id, and confirm that the interface returns a200 OKstatus code. - Retrieve keywords for a specified semiconductor segmented track, verify the track matching degree of the recall results, and adjust the corresponding configuration items to meet business requirements.
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.