Information Retrieval: Query types

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Note: the content of this post is mainly notes taken from professor Stefano Mizzaro’s lessons on (Web) Information Retrieval at Uniud.

There are 3 types of queries that an IRS can receive:

  1. Keyword based
  2. Pattern matching
  3. Structural

Keyword based

Can be divided in:

  • Single words — return documents that contain at least one of the words
  • Contextual — find words next to each other
  • Boolean — uses boolean operators
    • Usually it is relaxed by means of fuzzy boolean logic
  • Natural language — harder for the system, easier for the user.
    • Example: Conversational search of Siri, Alexa

Pattern matching

Can be divided in:

  • Words
  • Prefix — big part of the meaning is in the radix of the words, not at the end
  • Suffix — can lead to opposite results (example: “relevant”, “irrelevant”)
  • Substring
  • Range — very useful for dates and numbers. For text is not
  • RegExp — useful only for technical users (computer scientists…)
  • Extended pattern — simplified RegExps

In pattern matching it is good practice to allow errors, both in queries and in documents. Levenshtein distance can be used.


Based on the structure of the text. Since the web was invented they became more important. Can be divided in:

  • Fixed — email (sender, recipient, subject)
  • Hierarchical — book (chapter, section, subsection)
  • Hypertextual — non linear, linked documents contained in a graph

More query types

  • Query By Example
  • Spoken query
  • Long queries
  • Different UIs than search box only