「entity-resolution」の検索結果

Use this skill when configuring or troubleshooting Data Cloud identity resolution rulesets — matching rules, reconciliation rules, unified profiles, and cross-device identity linking. Trigger keywords: identity resolution ruleset, unified individual, match rule, reconciliation rule, unified profile, cross-device identity, Data Cloud deduplication, cluster creation. NOT for CRM duplicate and matching rules — use admin/duplicate-management. NOT for overall Data Cloud layer and activation design — use architect/data-cloud-architecture.

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Implement privacy-preserving record linkage across datasets using Bloom filter encoding, secure hash matching, threshold tuning for precision and recall, and false positive management. Enables entity resolution without exposing raw personally identifiable information between parties.

日本語の概要は準備中です。原文の説明を表示しています。

Knowledge graph specialist for entity and causal relationship modelingUse when "knowledge graph, graph database, falkordb, neo4j, cypher query, entity resolution, causal relationships, graph traversal, graph-database, knowledge-graph, falkordb, neo4j, cypher, entity-resolution, causal-graph, ml-memory" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Use when enabling Data Cloud (Data 360) in an org, creating data spaces, assigning permission sets, registering ingestion API sources, or configuring activation targets. Triggers: 'enable data cloud', 'data spaces setup', 'data cloud permission sets', 'ingestion API connected app', 'activation target setup', 'data cloud licensing', 'dedicated home org vs existing org'. NOT for data streams or DLO-to-DMO mapping — use data/data-cloud-data-streams. NOT for identity resolution rulesets — use admin/data-cloud-identity-resolution.

日本語の概要は準備中です。原文の説明を表示しています。

Guides AI agents through Senzing entity resolution workflows using the Senzing MCP server. Covers data mapping to Senzing format, SDK code generation (Python, Java, C#, Rust, TypeScript/Node.js), documentation search, error troubleshooting, sample data access, reporting and visualization, SDK setup guides, and V3-to-V4 migration. Use when working with entity resolution, record matching, record linkage, deduplication, Senzing SDK integration, data mapping for Senzing ingestion, or troubleshooting Senzing error codes. Also use when the user mentions matching records across data sources, finding duplicate entities, identity resolution, master data management, or needs to resolve who is who across datasets.

日本語の概要は準備中です。原文の説明を表示しています。