Time-Aware Query Solutions
Graphiti's time-aware functionality effectively solves the problem of analyzing data across time:
- time mark: Use when adding nodes
timestampThe parameter records the point in time, such asgraph.add_node(''Event'', name=''Product Launch'', timestamp=''2023-06-15'') - timing query: Time operators that use extensions of the Cypher syntax, such as
MATCH (e:Event) WHERE e.timestamp > ''2023-01-01'' RETURN e - Trend analysis: Combined
TEMPORAL PATHFunctions recognize patterns in entity relationships over time
Practical example: Retailers can compare the changes in the correlation of goods before and after holidays to identify seasonal consumption characteristics.
This answer comes from the articleGraphiti: dynamic knowledge graph construction and query tool (time-aware long memory scheme)The
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