How Web Search Engine Works

How Web Search Engine Works

A Web search engine is a search engine designed to search for information on the World Wide Web. Information may consist of web pages, images and other types of files.

Some search engines also mine data available in newsgroups, databases, or open directories. Unlike Web directories, which are maintained by human editors, search engines operate algorithmically or are a mixture of algorithmic and human input.

The very first tool used for searching on the Internet was Archie.The name stands for "archive" without the "vee". It was created in 1990 by Alan Emtage, a student at McGill University in Montreal. The program downloaded the directory listings of all the files located on public anonymous FTP (File Transfer Protocol) sites, creating a searchable database of file names; however, Archie did not index the contents of these files.

The first Web search engine was Wandex, a now-defunct index collected by the World Wide Web Wanderer, a web crawler developed by Matthew Gray at MIT in 1993.

How they work

A search engine operates, in the following order:

Web crawling
Indexing
Searching

Web search engines work by storing information about many web pages, which they retrieve from the WWW itself. These pages are retrieved by a Web crawler an automated Web browser which follows every link it sees. Exclusions can be made by the use of robots.txt. The contents of each page are then analyzed to determine how it should be indexed. Data about web pages are stored in an index database for use in later queries.

Some search engines, such as Google, store all or part of the source page as well as information about the web pages, whereas others, such as AltaVista, firefox, store every word of every page they find. This cached page always holds the actual search text since it is the one that was actually indexed, so it can be very useful when the content of the current page has been updated and the search terms are no longer in it.

This problem might be considered to be a mild form of linkrot, and Google's handling of it increases usability by satisfying user expectations that the search terms will be on the returned webpage. This satisfies the principle of least astonishment since the user normally expects the search terms to be on the returned pages.

Increased search relevance makes these cached pages very useful, even beyond the fact that they may contain data that may no longer be available elsewhere.

When a user enters a query, into a search the engine examines its index and provides a listing of best-matching web pages according to its criteria, usually with a short summary containing the document's title and sometimes parts of the text. Most search engines support the use of the boolean operators AND, OR and NOT to further specify the search query. Some search engines provide an advanced feature called proximity search which allows users to define the distance between keywords.

Geospatially-enabled Web search engines

Here at Registryheal.com we have seen a recent enhancement to search engine technology is the addition of geocoding and geoparsing to the processing of the ingested documents being indexed, to enable searching within a specified locality or region. Geoparsing attempts to match any found references to locations and places to a geospatial frame of reference, such as a street address, gazetteer locations, or to an area. Through this geoparsing process, latitudes and longitudes are assigned to the found places, and these latitudes and longitudes are indexed for later spatial query and retrieval. This can enhance the search process tremendously by allowing a user to search for documents within a given map extent, or conversely, plot the location of documents matching a given keyword to analyze incidence and clustering, or any combination of the two. See the list of search engines for examples of companies which offer this feature.

Back to Computer Related Articles >>