Vector Models and Indexing for Gas Marketing Content

Data is sourced from gas utility marketing management systems, official new media content libraries, and offline event planning archive files. Update

What data for this category looks like

Data is sourced from gas utility marketing management systems, official new media content libraries, and offline event planning archive files. Update cadence includes fixed-cycle updates and on-demand updates. Fixed-cycle updates correspond to quarterly community convenience activities and monthly promotional packages. On-demand updates correspond to temporary safety alerts and policy adjustment notices. Document structure includes unique identifier, publication channel, target user tags, main content, applicable service area, and effective time period fields. Some documents include associated gas service parameter fields.

What constraints these characteristics impose on vector models and indexing

Format differences across multi-channel sources require preprocessing steps to unify field formats, preventing vector calculation bias. The periodic update feature requires indexes to support incremental synchronization, avoiding resource waste from full index rebuilds. Structured fields such as applicable service area, effective time period, and target users must be jointly indexed with text vectors, otherwise non-matching content cannot be filtered. Attached service parameters must be included in the vectorization context to ensure matching between recalled content and associated services.

How to set configurations

Configuration ItemRecommended ValueRationale
vector_model_nametext-embedding-3-largeAdapts to the semantic complexity of gas marketing copy, supports fused vectorization of structured fields and text
index_chunk_size800–1200 charactersMatches the typical length range of gas marketing copy, avoids losing semantic associations from overly short splits, and reduces computational load from overly long splits
structured_filter_enabledEnabledSupports joint filtering of service_area, valid_period, target_demographic fields, to accurately match target users and service areas
incremental_index_triggerTriggered by data update timestampAdapts to on-demand updated marketing content, avoids redundant calculations and resource consumption from full indexing
recall_top_kTop 10 resultsBalances recall accuracy and system response speed, controls the input scale for subsequent reranking steps
vector_similarity_threshold0.75–0.85Filters low-correlation recall results, adapts to the semantic matching accuracy requirements of gas marketing content

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 case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.

Three common mistakes

  • Phenomenon: The number of index entries in a specified dataset increases without manual operation, and a single original index becomes multiple indexes. Cause: incremental_index_trigger is not configured to trigger by update timestamp. The system defaults to full synchronization of data sources, resulting in repeated indexing of already processed marketing content.
  • Phenomenon: The service becomes unresponsive when calling text-embedding-3-large, and the service fails to recover after restarting with the model configuration commented out. Cause: The index_timeout parameter is not set, causing vector calculation tasks to block indefinitely, and residual tasks are not cleaned up.
  • Phenomenon: Recall results include marketing content across service areas, and cannot accurately match local users. Cause: structured_filter_enabled is not enabled, and the service_area field is not included in the joint indexing rules.

How to confirm the configuration is correct

  • View the index_chunk_size parameter in the index management interface, confirm that the value falls within the range specified in the configuration table.
  • Submit a new marketing content piece, wait for indexing to complete, then perform a retrieval operation to verify that only content within the current effective time period is recalled.
  • Simulate a cross-service area retrieval request, verify that recall results automatically filter out non-target area copy.
  • Check system logs, confirm that only content with an update timestamp later than the last index is incrementally synchronized, with no duplicate index 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.