1.0 - 8.00 - PSALSA Example 4: Sources and Targets Tables as Inputs - Teradata Vantage

Teradata® Vantage Machine Learning Engine Analytic Function Reference

Teradata Vantage
Release Number
Release Date
May 2019
Content Type
Programming Reference
Publication ID
English (United States)

This example shows how to limit the vertices and edges used. Teradata recommends this technique if the original vertices and edges tables are large, but only a subset of the information is relevant. The function calculates the hubs and authorities for the nodes specified in the sources and targets tables (user_source_nodes and product_target_nodes).


As in PSALSA Example 3: User Similarity and Product Recommendation:
  • vertices: user_product_nodes, which has customer names
  • edges: women_apparel_log, which reflects customer shopping patterns

SQL Call

  ON user_product_nodes AS vertices PARTITION BY nodename
  ON women_apparel_log AS edges PARTITION BY username
  ON user_source_nodes AS sources PARTITION BY username
  ON product_target_nodes AS targets PARTITION BY product
  SourceKey ('username')
  TargetKey ('product')
  EdgeWeight ('frequency')
  MaxHubNum (2)
  MaxAuthorityNum (2)
  TeleportProb (0.15)
  RandomWalkLength (500)
) AS dt ORDER BY username, hub_score DESC, authority_score DESC;


Based on the output, the retailer recommends pajamas to Sandra, who has no purchase history for them, but recommends nothing to Susan, who has bought all the items (see the PSALSA Example 3: User Similarity and Product Recommendation input). The *_score results vary with every run.

username hub_username hub_score authority_product authority_score
Sandra     pajamas 0.333333333333333
Sandra Sally 0.214007782101167    
Sandra Susan 0.140077821011673    
Susan Stacie 0.206766917293233    
Susan Sally 0.176691729323308