Types of Queries in IR Systems

During the process of indexing, many keywords are associated with document set which contains words, phrases, date created, author names, and type of document. They are used by an IR system to build an inverted index which is then consulted during the search. The queries formulated by users are compared to the set of index keywords. Most IR systems also allow the use of Boolean and other operators to build a complex query. The query language with these operators enriches the expressiveness of a user’s information need. The Information Retrieval (IR) system finds the relevant documents from a large data set according to the user query. Queries submitted by users to search engines might be ambiguous, concise and their meaning may change over time. Some of the types of Queries in IR systems are – 1. Keyword Queries :

• Simplest and most common queries.
• The user enters just keyword combinations to retrieve documents.
• These keywords are connected by logical AND operator.
• All retrieval models provide support for keyword queries.

2. Boolean Queries :

• Some IR systems allow using +, -, AND, OR, NOT, ( ), Boolean operators in combination of keyword formulations.
• No ranking is involved because a document either satisfies such a query or does not satisfy it.
• A document is retrieved for boolean query if it is logically true as exact match in document.

3. Phrase Queries :

• When documents are represented using an inverted keyword index for searching, the relative order of items in document is lost.
• To perform exact phase retrieval, these phases are encoded in inverted index or implemented differently.
• This query consists of a sequence of words that make up a phase.
• It is generally enclosed within double quotes.

4. Proximity Queries :

• Proximity refers to search that accounts for how close within a record multiple items should be to each other.
• Most commonly used proximity search option is a phase search that requires terms to be in exact order.
• Other proximity operators can specify how close terms should be to each other. Some will specify the order of search terms.
• Search engines use various operators names such as NEAR, ADJ (adjacent), or AFTER.
• However, providing support for complex proximity operators becomes expensive as it requires time-consuming pre-processing of documents and so it is suitable for smaller document collections rather than for web.

5. Wildcard Queries :

• It supports regular expressions and pattern matching-based searching in text.
• Retrieval models do not directly support for this query type.
• In IR systems, certain kinds of wildcard search support may be implemented. Example: usually words ending with trailing characters.

6. Natural Language Queries :

• There are only a few natural language search engines that aim to understand the structure and meaning of queries written in natural language text, generally as question or narrative.
• The system tries to formulate answers for these queries from retrieved results.
• Semantic models can provide support for this query type.