What the Data for This Category Looks Like
The data for game industry intelligent due diligence reports primarily comes from national press and publication administration version approval documents, public operation reports from game developers, and third-party industry monitoring reports. There are two update cycles: structured operation data is synchronized monthly, and compliance-related documents for version approvals are updated alongside approval milestones. The document structure includes two categories: structured CSV files with fields including game ID, name, development entity, launch date, core gameplay tags, and other fields; unstructured documents including version approval replies, compliance review records, and competitor analysis summaries. Field units are mostly concrete units such as "person", "yuan", "day", with no complex nested formats.
What Constraints These Characteristics Impose on Retrieval and Recall
The structured nature of due diligence data requires retrieval to prioritize matching specified fields, rather than using general semantic recall, to avoid mixing irrelevant results. Monthly updated operation data requires the knowledge base to set a fixed refresh cycle to ensure the timeliness of recalled content. The strong timeliness of version approval compliance documents requires limiting the valid duration of recalled content to prevent returning expired approval information. Multi-label core gameplay fields need to support combined retrieval logic to accommodate detailed query needs for game categories. Additionally, encoding adaptation for Chinese structured CSV files must be implemented to avoid garbled characters that cause field recognition failures and impact retrieval accuracy.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
PARSE_CSV_ENCODING | UTF-8 | Adapts to the Chinese CSV file encoding commonly used for game due diligence, preventing garbled field display |
RECALL_TOP_K | Top 10 results | Game due diligence queries mostly rely on precise field matching, and a small number of recalled results can cover core needs |
SPLIT_CHUNK_SIZE | 800–1200 characters | Game due diligence documents include long sections of operation data descriptions and compliance text, this length preserves complete field association logic |
VECTOR_STORE_TYPE | Field-based indexing | Most game due diligence data consists of structured fields, and field-based indexing improves precise retrieval efficiency |
DOC_REFRESH_INTERVAL | 30 days | Game operation data is updated monthly, a 30-day refresh cycle matches the data update rhythm |
SIMILARITY_THRESHOLD | 0.75–0.85 | Game category query keywords are mostly precise terms, this range filters out irrelevant recalled results |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Issue: Garbled field display in the knowledge base after uploading a Chinese CSV file. Cause: The
PARSE_CSV_ENCODINGconfiguration is not set toUTF-8, and the default encoding cannot adapt to Chinese encoding formats. - Issue: Expired version approval documents appear in retrieval results. Cause: The
DOC_REFRESH_INTERVALparameter is not set, or the refresh cycle is set too long, causing outdated documents to not be cleaned up. - Issue: Irrelevant gameplay description documents are returned when querying game revenue data. Cause: The field-based indexing vector storage configuration is not enabled, and only full-text semantic retrieval is used, failing to accurately match revenue fields.
How to Verify Successful Configuration
- A test Chinese CSV file may be uploaded, and field display can be verified to confirm the
PARSE_CSV_ENCODINGconfiguration is active. - A query containing game revenue fields may be submitted, and recalled results can be verified to only include documents related to the target fields, confirming the field-based indexing configuration is active.
- Knowledge base refresh logs may be reviewed to confirm the document refresh cycle matches the preset time interval, verifying the
DOC_REFRESH_INTERVALparameter is configured correctly. - A query containing combined gameplay tags may be submitted, and recall of documents with the corresponding tags can be checked to confirm the combined retrieval logic is active.
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.