## Boolean Searching on the Internet

Most library database searching. is based on the principles of Boolean logic. Boolean logic refers to the logical relationship among search terms, and is named for the British mathematician George Boole.

Boolean logic consists of three logical operators:

• OR
• AND
• NOT
Each operator can be visually described by using Venn diagrams, as shown below.

OR

college OR university

Query:    I would like information about college.

• In this search, we will retrieve records in which AT LEAST ONE of the search terms is present.

• This is illustrated by:

• the shaded circle with the word college representing all the records that contain the word "college"

• the shaded circle with the word university representing all the records that contain the word "university"

• the shaded overlap area representing all the records that contain both "college" and "university"

OR logic is most commonly used to search for synonymous terms or concepts.

Here is an example of how OR logic works:

Search terms Results
college 17,320,770
university 33,685,205
college OR university 33,702,660

OR logic collates the results to retrieve all the unique records containing one term, the other, or both.

The more terms or concepts we combine in a search with OR logic, the more records we will retrieve.

For example:

Search terms Results
college 17,320,770
university 33,685,205
college OR university 33,702,660
college OR university OR campus 33,703,082

AND

poverty AND crime

Query:    I'm interested in the relationship between poverty and crime.

• In this search, we retrieve records in which BOTH of the search terms are present

• This is illustrated by the shaded area overlapping the two circles representing all the records that contain both the word "poverty" and the word "crime"

• Notice how we do not retrieve any records with only "poverty" or only "crime"

Here is an example of how AND logic works:

Search terms Results
poverty 783,447
crime 2,962,165
poverty AND crime 1,677

The more terms or concepts we combine in a search with AND logic, the fewer records we will retrieve.

For example:
Search terms Results
poverty 783,447
crime 2,962,165
poverty AND crime 1,677
poverty AND crime AND gender 76

A few Internet search engines make use of the proximity operator NEAR. A proximity operator determines the closeness of terms within a source document. NEAR is a restrictive AND. The closeness of the search terms is determined by the particular search engine. For example:

• NEAR in AltaVista (Power Search) is 10 words
• NEAR in Lycos (Lycos Pro) is 25 words

NOT

cats NOT dogs

Query:    I want to see information about cats, but I want to avoid seeing anything about dogs.

• In this search, we retrieve records in which ONLY ONE of the terms is present

• This is illustrated by the shaded area with the word cats representing all the records containing the word "cats"

• No records are retrieved in which the word "dogs" appears, even if the word "cats" appears there too

Here is an example of how NOT logic works:

Search terms Results
cats 3,651,252
dogs 4,556,515
cats NOT dogs 81,497

NOT logic excludes records from your search results. Be careful when you use NOT: the term you do want may be present in an important way in documents that also contain the word you wish to avoid.

Examples:

Query:    I need information about cats.

Boolean logic:    OR

Search:    cats OR felines

Query:    I'm interested in dyslexia in adults.

Boolean logic:    AND

Boolean logic:    NOT