What data for this category looks like
Game investment research data sources include game publisher public financial report excerpts, National Press and Publication Administration game license announcement documents, third-party game monitoring platform operation data, game development team public iteration logs, and player community discussion content. Update rhythm: License announcements are released in fixed batches. Operating revenue data updates weekly. Development logs are released irregularly alongside version iterations. Community public opinion updates in real time. Document structures include structured tabular data, semi-structured analyst meeting minutes, and unstructured community discussion posts. Fields include approval number, game name, approval date, revenue category, monitoring cycle, and more. Units include ten thousand yuan, natural day, batch number, and more.
What constraints these characteristics impose on knowledge base retrieval and recall
Structured license lists and revenue classification tables require field-level precise matching to avoid fuzzy recall interfering with results. Real-time updated community public opinion and irregularly released development logs require support for incremental indexing and scheduled refreshing to ensure the timeliness of recalled content. Mixed documents from multiple sources have format differences, so different parsing rules must be adapted to uniformly extract valid information. Detailed investment research questions often involve specific fields. The field matching degree between recalled results and questions should take priority. Relying solely on text semantic similarity is not enough to cover precise retrieval needs.
Configuration settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
RECALL_TOP_K | Top 10-15 results | Game investment research documents mostly cover niche topics. Too many recalled results will introduce irrelevant information, while too few will fail to cover effective retrieval scope |
SIMILARITY_THRESHOLD | 0.72-0.80 | Game investment research questions often involve specific field matching. A threshold that is too low will recall irrelevant documents, while a threshold that is too high will miss valid content |
PARSE_TABLE_ENABLE | Enabled | Game investment research contains a large amount of structured tabular data. Enabling this option can extract fields for precise retrieval and improve matching accuracy |
INDEX_REFRESH_INTERVAL | Every 6 hours | Balances the timeliness of community public opinion and the batch update rhythm of license announcements, and avoids resource consumption from full index rebuilding |
INCREMENTAL_SYNC_ENABLE | Enabled | Development logs are updated irregularly with version iterations. Incremental synchronization avoids full index rebuilding and improves update efficiency |
CHUNK_SIZE | 800-1200 characters | Analyst meeting minutes for game investment research are mostly long texts. The segment length adapts to semantic association requirements, avoiding losing context if too long or increasing retrieval redundancy if too short |
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 configuration mistakes
- In multi-knowledge base classification scenarios for version v4.8.3, classification results only depend on the current question text and do not associate with historical context, ultimately being assigned to the fallback category. The cause is that the context-associated classification parameter is not configured, or the parameter value does not cover the historical conversation length.
- After uploading image files, the knowledge base cannot extract valid retrieval content, and retrieval results are empty. The cause is that the image parsing related configuration is not enabled, or only text file parsing is supported currently.
- A large amount of irrelevant community discussion content is mixed in retrieval results, which does not match the target license or revenue data. The cause is that no field-level retrieval rules are set, and only global semantic similarity is relied on, leading to matching deviation.
How to verify correct configuration
- Upload a structured game license table file, run retrieval for questions related to the license status of a specific game, and check whether the returned results contain corresponding field information.
- Submit an updated development log file, run retrieval for questions related to the development content of the corresponding version, and check whether the returned results contain the latest updated content.
- After configuring classification parameters, submit a test question with historical context, and check whether the classification results match the expected category.
- View the index refresh log to confirm that the incremental synchronization task is executed according to the set cycle, with no failed records.
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.