Categories are a very important feature offered to our News API customers. In the last 3 months, we found that 70% of our customer base use categories in more than 60% of their queries and that's a lot of queries. In a recent survey, most of our customers informed us that they would like access to a more extensive taxonomy of Categories than we have offered up to this point. It is for these reasons that we are proud to announce the launch of our new Smart Tagger features. 

With a taxonomy of ~3,000 topical categories and ~1,500 industries, Smart Tagger classifies our articles with high precision, making it easier for you to filter for articles most relevant to you and your use cases.  

But how can you benefit the most from the Smart Tagger? You can read more about the benefits of Smart Tagger in our feature announcement blog and here we will guide you through some example queries, showing you how easy it is to start discovering the market impact events and stories that matter to you.

Smart Tagger Parameters - Docs

With Smart Tagger, articles are filtered for industries and categories using the industries and categories parameters. They are used in conjunction with our new Aylien Querying Language, or AQL. Both industries and categories come with a number of sub-parameters that can be used to further filter your query results. 

 Parameter     Description

  Used with


Unique category identifier.

categories and industries. Note that with industries, there is no need to prefix the industry id value with the id parameter.
 label Unique category label or name. categories and industries. Note that with industries, there is no need to prefix the industry label value with the label parameter.
 taxonomy The name of the taxonomy that that category in question belongs to. For Smart Tagger categories, the taxonomy is aylien. categories
 score A confidence score ranging from 0 to 1, indicating how relevant the category tag is to an article. categories and industries


A parameter that indicates what value the articles should be sorted by. Typically, the sort_by() is used in conjunction with the score parameter.

categories and industries


Below is an example of the syntax used to write an AQL query that includes Smart Tagger industries and categories parameters. 

opts = {'aql': '(categories:{{id: category_id AND taxonomy:aylien AND score:[0.7 TO *]}}) AND

industries: {{"industry label" AND score: [0.9 TO *] sort_by(score)}}'}

Smart Tagger in Action

1. Tracking ESG events for the oil and gas industry

Using the Smart Tagger categories taxonomy, you can now filter for stories tagged with a myriad of industries and risk-related categories. To see our complete list of categories, you can request access to Smart Tagger. In this example, we will construct a query that filters for articles tracking ESG-related events, focused on the oil and gas industry.

opts = {'aql': '(categories:{{id:(ay.lifesoc.esg) AND taxonomy:aylien AND score:[0.7 TO 1]}}) AND

industries: {{ AND score: [0.9 TO *] sort_by(score)}}'}

In the query above, we apply 3 category parameters and 3 industry parameters within the AQL parameter set. For categories, we use the id, taxonomy, and score parameters to filter for articles tagged with the ay.lifesoc.esg (Environmental, Social and Governance) category, a category in the Smart Tagger aylien taxonomy, filtering out any articles with a category confidence score less than 0.7. In place of id, we could use the label parameter with the value "Environmental, Social and Governance". 

Within the AQL parameter set, we also apply filters to the query to retrieve articles relating to the (Oil and Gas Production and Operations) industry, filtering out any articles with an industry confidence score less than 0.9. 

Take a look at the top 5 results for this query that are super relevant to oil and gas companies within the context of ESG, highlighting the quality of results we retrieve when filtering using Smart Tagger.

Sample Articles - ESG

      Article Title


  Huntington oil spill and its greasy aftermath
2   As Western Oil Giants Cut Production, State-Owned Companies Step Up
3   Russia: Rosneft sells 5 per cent in Vostok Oil to a consortium of Vitol and   MME
4   Chesapeake Utilities Corporation Completes Construction of Noble Road Landfill Renewable Natural Gas Transportation Project
5   Bellona cheers EU proposal to leave Arctic oil, coal and gas in the ground

2. Tracking criminal activity in the financial sector

Another real-world example for Smart Tagger features is tracking criminal events in the finance world. The query below is an example of how this can be achieved.

opts = {'aql': 'categories:{{taxonomy:aylien AND score:[0.8 TO *] AND}} AND

industries: {{"Financial Services and Banking" AND score: [0.9 TO *] sort_by(score)}}'}

In this example, we filter for articles tagged with (Business Crime) and the Financial Services and Banking industry, ensuring that each article has a category confidence score greater than 0.8 and an industries score of at least 0.9. Once again, the top 5 articles from this search clearly demonstrate the power of Smart Tagger when used to track impactful events.

Sample Articles - Financial crime in financial services

     Article Title
1 Police Officer Indicted on Federal Bank Fraud Charge Involving Paycheck Protection Program Loans
2 Appeals court overturns Bank of Oswego fraud convictions
3 New York court rejects Nirav Modi's plea seeking dismissal of fraud charges
4 NY Man Sentenced For $1.1 Million Bank Loan, Credit Card Fraud Schemes
5 Florida Man Pleads Guilty to Payment Processing Fraud Scheme


The benefits of Smart Tagger are clearly seen in our 2 simple examples. If you would like to learn more about Smart Tagger, or to arrange a demonstration of some real-world example queries relevant to you click the link below. In the meantime, you can read more about how to get the most out of these features in our documentation, or sign up for a free trial in order to access Smart Tagger.

NEWS API - Smart Tagger

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