Skip to main content

Overview

Matching strategies control how Experio identifies duplicate or related entities across different data sources. When the same person, project, or organization appears in multiple documents, matching strategies determine whether they should be merged into a single entity or kept separate. Navigate to Admin > Graph > Matching Strategies.

Strategy Types

Default Strategy

The default strategy applies to all entity types unless overridden. It defines the baseline matching behavior for your entire knowledge graph.

Entity-Specific Strategies

Create custom strategies for specific entity types that need different matching rules. For example, person names may need fuzzy matching, while project codes need exact matching.

Configuration Sections

Each matching strategy has four configuration areas:

1. Matching Methods

Enable and weight different matching algorithms:
MethodDescription
ExactCase-insensitive exact string match
Vector SimilaritySemantic similarity using vector embeddings
FuzzyApproximate string matching (handles typos, abbreviations)
PhoneticSound-based matching (handles spelling variations)
SynonymMatches using defined synonym lists
Each enabled method has a weight slider (0 to 1) that controls its relative importance in the overall match score.

2. Filters

Apply additional constraints to matching: Temporal Filter:
  • Max Distance (Days) — Maximum time difference between entities (default: 1825 / 5 years)
  • Penalty Per Year — Score reduction per year of difference (default: 0.1)
  • Date Attribute Names — Which entity attributes contain dates
Relationship Filter:
  • Parent Entity Types — Limit matching to entities with specific parent types
  • Relationship Types — Consider only entities connected by specific relationships

3. Normalization

Preprocessing steps applied before matching:
OptionDescription
Unicode NormalizationStandardize unicode characters
Remove PrefixesStrip “The”, “A”, “An” from entity names
Remove Company SuffixesStrip “Inc”, “LLC”, “Corp”, etc.
Expand AbbreviationsExpand common abbreviations to full forms
Punctuation NormalizationStandardize punctuation

4. Thresholds

Define confidence levels that determine how matches are handled:
ThresholdDefaultBehavior
Auto-Match0.9Matches above this score are merged automatically
LLM Disambiguation0.7Matches in this range are sent to the AI for review
Human Review0.5Matches in this range are queued for manual review
Matches below the Human Review threshold are treated as distinct entities.

Creating Entity-Specific Strategies

  1. Click Create New Strategy
  2. Select the entity type this strategy applies to
  3. Configure matching methods, filters, normalization, and thresholds
  4. Save the strategy
The entity-specific strategy overrides the default for that entity type only.

Resetting to Defaults

Each strategy section can be reset to default values using the Reset option. This is useful if experimental changes produce poor results.