What is Search Algorithm?

Search Algorithm

In very general terms, a search algorithm is a problem-solving procedure that takes a problem, evaluates a number of possible answers, and then returns the solution to that problem. A search algorithm for a search engine takes the problem (the word or phrase being searched for), sifts through a database that contains cataloged keywords and the URLs those words are related to, and then returns pages that contain the word or phrase that was searched for, either in the body of the page or in a URL that points to the page.

There are several classifications of search algorithms, and each search engine uses algorithms that are slightly different. That’s why a search for one word or phrase will yield different results from different search engines. Some of the most common types of search algorithms include the following:

• List Search: 

A list search algorithm searches through specified data looking for a single key. The data is searched in a very linear, list-style method. The result of a list search is usually a single element, which means that searching through billions of web sites could be very time-consuming, but would yield a smaller search result. 

• Tree Search: 

Envision a tree in your mind. Now, examine that tree either from the roots out or from the leaves in. This is how a tree search algorithm works. The algorithm searches a data set from the broadest to the most narrow, or from the most narrow to the broadest. Data sets are like trees; a single piece of data can branch to many other pieces of data, and this is very much how the Web is set up. Tree searches, then, are more useful when conducting searches on the Web, although they are not the only searches that can be successful.

• SQL Search:

One of the difficulties with a tree search is that it’s conducted in a hierarchical manner, meaning it’s conducted from one point to another, according to the ranking of the data being searched. A SQL (pronounced See-Quel) search allows data to be searched in a non-hierarchical manner, which means that data can be searched from any subset of data.

• Informed Search: 

An informed search algorithm looks for a specific answer to a specific problem in a tree-like data set. The informed search, despite its name, is not always the best choice for web searches because of the general nature of the answers being sought. Instead, informed search is better used for specific queries in specific data sets.

• Adversarial Search: 

An adversarial search algorithm looks for all possible solutions to a problem, much like finding all the possible solutions in a game. This algorithm is difficult to use with web searches, because the number of possible solutions to a word or phrase search is nearly infinite on the Web.

• Constraint Satisfaction Search:  

When you think of searching the Web for a word or phrase, the constraint satisfaction search algorithm is most likely to satisfy your desire to find something. In this type of search algorithm, the solution is discovered by meeting a set of constraints, and the data set can be searched in a variety of different ways that do not have to be linear. Constraint satisfaction searches can be very useful for searching the Web.