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Overview

Advanced querying techniques allow users to construct sophisticated search queries, enabling efficient retrieval of precise and relevant news content. These techniques are crucial for productive information extraction from the vast database of articles available through the API.

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Key querying techniques

In the context of the NewsCatcher News API v3, advanced querying techniques refer to using specific syntax and operators within the q parameter to create complex, highly targeted search queries. These techniques include exact matching, boolean operators, wildcards, and proximity-based searching.

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Exact match (“double quotes”)

Use double quotes to search for an exact phrase or name.
  • Syntax: "phrase or name"
  • Example: q="Tim Cook"
  • Use case: Always use double quotes for company names, person names, and specific phrases.
Without quotes, the query is treated as individual terms combined with the AND operator. For example, q=Tim Cook is equivalent to q=Tim AND Cook.

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Escaping double quotes in JSON queries

To use exact match syntax in JSON queries, you must escape double quotes by adding a backslash \ before each double quote. This ensures the JSON is valid and the query is interpreted correctly. Example: 
{
  "q": "presidential election",
  "PER_entity_name": "\"Kamala Harris\" AND \"Donald Trump\"",
  "include_nlp_data": true
}
Always use backslashes \ before double quotes within query strings to maintain exact match syntax in JSON.

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Boolean operators

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AND

  • Ensures all specified terms are present in the text.
  • It’s the default operator when multiple words are used without quotes.
  • Syntax: term1 AND term2 or simply term1 term2
  • Example: q=Microsoft AND Tesla or q=Microsoft Tesla

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OR

  • Matches articles containing either of the specified terms.
  • Syntax: term1 OR term2
  • Example: q=(Apple AND Cook) OR (Microsoft AND Gates)

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NOT

  • Excludes articles containing the specified term.
  • Syntax: term1 NOT term2
  • Example: q=Tesla NOT "Elon Musk"

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Wildcards (* and ?)

  • *: Matches any string of any length.
  • ?: Matches any single character.
  • Example: q=Microsoft AND C?O (matches CEO, CFO, CTO, etc.)

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Proximity-based search (NEAR)

The NEAR operator finds articles where specified terms appear close to each other.
  • Syntax: NEAR("phrase_A", "phrase_B", distance, in_order)
  • Example: q=NEAR("browser", "Edge", 15)
  • This finds articles where “browser” and “Edge” appear within 15 words of each other.
  • If the in_order parameter (default: false) can ensure phrase_B appears after phrase_A when set to true.
Limitations:
  • Maximum 4 words per phrase
  • Maximum 3 phrases per NEAR operation
  • Maximum distance of 100 words

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Best practices

  1. Start with broader searches and refine as needed.
  2. Use double quotes for companies, person names, and specific phrases.
  3. Use parentheses to group related terms in complex queries with boolean operators.
  4. Utilize NEAR to find related terms within a specific context.
  5. URL-encode the q parameter in GET requests to prevent issues with special characters.
  6. Check the user_input field in the JSON response to confirm the correct interpretation of your keywords.
  7. Combine multiple techniques for more precise results.

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Examples of complex queries

  • Market Research:
q="artificial intelligence" AND (healthcare OR "medical research") AND NEAR("market growth", "emerging trends", 20)
  • Competitive Analysis:
q=("Apple" OR "Google") AND "smartphone market" AND NOT ("Samsung" OR "Huawei")
  • Event Monitoring:
q=("climate change" OR "global warming") AND (conference* OR summit) AND NEAR("Paris agreement", implementation, 15)

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Comparison of techniques

TechniqueStrengthsLimitationsBest For
Exact MatchPrecise phrase matchingMay miss relevant variationsSpecific names or phrases
Boolean OperatorsVersatile, combines multiple conceptsCan become complexComprehensive searches
WildcardsBroadens search to include variationsCan return irrelevant resultsExploring related terms
Proximity-Based Search (NEAR)Finds related terms in contextLimited to 100-word distanceConcept relationships