question

Upvotes
Accepted
1.2k 8 11 8

How can I find all entities related to a set of articles tagged with TRIT with high relevance?

I'm looking for articles that TRIT tagged with silver or gold social tags terms. I only want to see articles that TRIT scored highly for each tag and all related entities to that set of articles.

data-fusionintelligent-tagging
icon clock
10 |1500

Up to 2 attachments (including images) can be used with a maximum of 512.0 KiB each and 1.0 MiB total.

1 Answer

· Write an Answer
Upvotes
Accepted
1.2k 8 11 8

In Data Fusion we're flattening the TRIT model for convenience, hence duplication of properties. So a query for gold or silver tagged articles with a high score would use a solr syntax

(SocialTag_attr:"silver" OR SocialTag_attr:"gold") AND (calais_confidence_80_attr:"silver" OR calais_confidence_80_attr:"gold")` 
GET /datafusion/api/entity/search?searchString=(SocialTag_attr:%22silver%22%20OR%20SocialTag_attr:%22gold%22)%20AND%20(calais_confidence_80_attr:%22silver%22%20OR%20calais_confidence_80_attr:%22gold%22)&extraFields=SocialTag_attr%2Ccalais_confidence_80_attr 

We can then tokenize this search so that we can refer to it as a set in subsequent calls.

GET /datafusion/api/entity/search/tokenize?searchString=(SocialTag_attr:%22silver%22%20OR%20SocialTag_attr:%22gold%22)%20AND%20(calais_confidence_80_attr:%22silver%22%20OR%20calais_confidence_80_attr:%22gold%22)

Example response

{
  "tokenPart": "183cfc09cb7131534d38bef1d015721e",
  "count": 155
}

And use that token to pull all entities related to a set of articles returned for our initial gold or silver article query.

GET /datafusion/api/entity/search?parentUris=183cfc09cb7131534d38bef1d015721e&includePredicates=true&extraFields=*
icon clock
10 |1500

Up to 2 attachments (including images) can be used with a maximum of 512.0 KiB each and 1.0 MiB total.

Write an Answer

Hint: Notify or tag a user in this post by typing @username.

Up to 2 attachments (including images) can be used with a maximum of 512.0 KiB each and 1.0 MiB total.