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History

History

Timeline (full list)

Year

Engine

Event

1993

W3Catalog

Launch

Aliweb

Launch

JumpStation

Launch

1994

WebCrawler

Launch

Infoseek

Launch

Lycos

Launch

1995

AltaVista

Launch

Open Text Web Index

Launch

Magellan

Launch

Excite

Launch

SAPO

Launch

1996

Dogpile

Launch

Inktomi

Founded

HotBot

Founded

Ask Jeeves

Founded

1997

Northern Light

Launch

Yandex

Launch

1998

Google

Launch

1999

AlltheWeb

Launch

GenieKnows

Founded

Naver

Launch

Teoma

Founded

Vivisimo

Founded

2000

Baidu

Founded

Exalead

Founded

2003

Info.com

Launch

2004

Yahoo! Search

Final launch

A9.com

Launch

Sogou

Launch

2005

MSN Search

Final launch

Ask.com

Launch

GoodSearch

Launch

SearchMe

Founded

2006

wikiseek

Founded

Quaero

Founded

Ask.com

Launch

Live Search

Launch

ChaCha

Beta Launch

Guruji.com

Beta Launch

2007

wikiseek

Launched

Sproose

Launched

Wikia Search

Launched

Blackle.com

Launched

2008

Powerset

Launched

Picollator

Launched

Viewzi

Launched

Cuil

Launched

Boogami

Launched

LeapFish

Beta Launch

Forestle

Launched

VADLO

Launched

Sperse! Search

Launched

Duck Duck Go

Launched

2009

Bing

Launched

Yebol

Beta Launch

Mugurdy

Launched

Goby

Launched

During the early development of the web, there was a list of webservers edited by Tim Berners-Lee and hosted on the CERN webserver. One historical snapshot from 1992 remains. As more webservers went online the central list could not keep up. On the NCSA site new servers were announced under the title "What's New!"

The very first tool used for searching on the Internet was Archie. The name stands for "archive" without the "v." 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 sites.

The rise of Gopher (created in 1991 by Mark McCahill at the University of Minnesota) led to two new search programs, Veronica and Jughead. Like Archie, they searched the file names and titles stored in Gopher index systems. Veronica (Very Easy Rodent-Oriented Net-wide Index to Computerized Archives) provided a keyword search of most Gopher menu titles in the entire Gopher listings. Jughead (Jonzy's Universal Gopher Hierarchy Excavation And Display) was a tool for obtaining menu information from specific Gopher servers. While the name of the search engine "Archie" was not a reference to the Archie comic book series, "Veronica" and "Jughead" are characters in the series, thus referencing their predecessor.

In the summer of 1993, no search engine existed yet for the web, though numerous specialized catalogues were maintained by hand. Oscar Nierstrasz at the University of Geneva wrote a series of Perl scripts that would periodically mirror these pages and rewrite them into a standard format which formed the basis for W3Catalog, the web's first primitive search engine, released on September 2, 1993.

In June 1993, Matthew Gray, then at MIT, produced what was probably the first web robot, the Perl-based World Wide Web Wanderer, and used it to generate an index called 'Wandex'. The purpose of the Wanderer was to measure the size of the World Wide Web, which it did until late 1995. The web's second search engine Aliweb appeared in November 1993. Aliweb did not use a web robot, but instead depended on being notified by website administrators of the existence at each site of an index file in a particular format.

JumpStation (released in December 1993) used a web robot to find web pages and to build its index, and used a web form as the interface to its query program. It was thus the first WWW resource-discovery tool to combine the three essential features of a web search engine (crawling, indexing, and searching) as described below. Because of the limited resources available on the platform on which it ran, its indexing and hence searching were limited to the titles and headings found in the web pages the crawler encountered.

One of the first "full text" crawler-based search engines was WebCrawler, which came out in 1994. Unlike its predecessors, it let users search for any word in any webpage, which has become the standard for all major search engines since. It was also the first one to be widely known by the public. Also in 1994 Lycos (which started at Carnegie Mellon University) was launched, and became a major commercial endeavor.

Soon after, many search engines appeared and vied for popularity. These included Magellan, Excite, Infoseek, Inktomi, Northern Light, and AltaVista. Yahoo! was among the most popular ways for people to find web pages of interest, but its search function operated on its web directory, rather than full-text copies of web pages. Information seekers could also browse the directory instead of doing a keyword-based search.

In 1996, Netscape was looking to give a single search engine an exclusive deal to be their featured search engine. There was so much interest that instead a deal was struck with Netscape by 5 of the major search engines, where for $5Million per year each search engine would be in a rotation on the Netscape search engine page. These five engines were: Yahoo!, Magellan, Lycos, Infoseek and Excite.

Search engines were also known as some of the brightest stars in the Internet investing frenzy that occurred in the late 1990s. Several companies entered the market spectacularly, receiving record gains during their initial public offerings. Some have taken down their public search engine, and are marketing enterprise-only editions, such as Northern Light. Many search engine companies were caught up in the dot-com bubble, a speculation-driven market boom that peaked in 1999 and ended in 2001.

Around 2000, the Google search engine rose to prominence.[citation needed] The company achieved better results for many searches with an innovation called PageRank. This iterative algorithm ranks web pages based on the number and PageRank of other web sites and pages that link there, on the premise that good or desirable pages are linked to more than others. Google also maintained a minimalist interface to its search engine. In contrast, many of its competitors embedded a search engine in a web portal.

By 2000, Yahoo was providing search services based on Inktomi's search engine. Yahoo! acquired Inktomi in 2002, and Overture (which owned AlltheWeb and AltaVista) in 2003. Yahoo! switched to Google's search engine until 2004, when it launched its own search engine based on the combined technologies of its acquisitions.

Microsoft first launched MSN Search in the fall of 1998 using search results from Inktomi. In early 1999 the site began to display listings from Looksmart blended with results from Inktomi except for a short time in 1999 when results from AltaVista were used instead. In 2004, Microsoft began a transition to its own search technology, powered by its own web crawler (called msnbot).

Microsoft's rebranded search engine, Bing, was launched on June 1, 2009. On July 29, 2009, Yahoo! and Microsoft finalized a deal in which Yahoo! Search would be powered by Microsoft Bing technology.

According to Hitbox, Google's worldwide popularity peaked at 82.7% in December, 2008. July 2009 rankings showed Google (78.4%) losing traffic to Baidu (8.87%), and Bing (3.17%). The market share of Yahoo! Search (7.16%) and AOL (0.6%) were also declining.

In the United States, Google held a 63.2% market share in May 2009, according to Nielsen NetRatings. In the People's Republic of China, Baidu held a 61.6% market share for web search in July 2009.

Search engines enable the discovery of sources like documents which existence was not generally known. In January 2010, a previously unknown letter from the French philosopher Ren Descartes, dated May 27, 1641, was found by the Dutch philosopher Theo Verbeek when browsing through Google. Bos found the letter mentioned in a summary of autographs kept by a college in Haverford, Pennsylvania. This was the third letter by Descartes found in the last 25 years .

How web search engines work

This section does not cite any references or sources.

Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. (November 2007)

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 html itself. These pages are retrieved by a Web crawler (sometimes also known as a spider) an automated Web browser which follows every link on the site. 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 (for example, words are extracted from the titles, headings, or special fields called meta tags). Data about web pages are stored in an index database for use in later queries. A query can be a single word. The purpose of an index is to allow information to be found as quickly as possible. Some search engines, such as Google, store all or part of the source page (referred to as a cache) as well as information about the web pages, whereas others, such as AltaVista, 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 engine (typically by using key words), 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. The index is built from the information stored with the data and the method by which the information is indexed. Unfortunately, there is not one search engine that allows to search documents by date. Most search engines support the use of the boolean operators AND, OR and NOT to further specify the search query. Boolean operators are for literal searches that allow the user to refine and extend the terms of the search. The engine looks for the words or phrases exactly as entered. Some search engines provide an advanced feature called proximity search which allows users to define the distance between keywords. There is also concept-based searching where the research involves using statistical analysis on pages containing the words or phrases you search for. As well, natural language queries allow the user to type a question in the same form one would ask it to a human. A site like this would be ask.com.

The usefulness of a search engine depends on the relevance of the result set it gives back. While there may be millions of web pages that include a particular word or phrase, some pages may be more relevant, popular, or authoritative than others. Most search engines employ methods to rank the results to provide the "best" results first. How a search engine decides which pages are the best matches, and what order the results should be shown in, varies widely from one engine to another. The methods also change over time as Internet usage changes and new techniques evolve. There are two main types of search engine that have evolved: one is a system of predefined and hierarchically ordered keywords that humans have programmed extensively. The other is a system that generates an "inverted index" by analyzing texts it locates. This second form relies much more heavily on the computer itself to do the bulk of the work.

Most Web search engines are commercial ventures supported by advertising revenue and, as a result, some employ the practice of allowing advertisers to pay money to have their listings ranked higher in search results. Those search engines which do not accept money for their search engine results make money by running search related ads alongside the regular search engine results. The search engines make money every time someone clicks on one of these ads.

Game search engines

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Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. (December 2009)

A game search engine is similar to a web search engine, but it only includes results related to the video game industry. The growing market of video game industry demands a more specific search platform to find game information, game resources, game videos, game blogs and bloggers, game download websites and importantly game industry news.

Some specialist websites have incorporated a search facility that only brings in game related results. Examples include GamePublic, Gamespot, KakaGames, and GameSpider.

Also in existence are video game specific search engines based on Google custom searches. Examples include AllGameSearch and GameCurry.

See also

Collaborative search engine

Enterprise search

List of search engines

Internet

Metasearch engine

Natural language search engine

OpenSearch

Search engine marketing

Search engine optimization

Search oriented architecture

Selection-based search

Semantic Web

Social search

Spell checker

Web indexing

Web search query

Website Parse Template

References

GBMW: Reports of 30-day punishment, re: Car maker BMW had its German website bmw.de delisted from Google, such as: Slashdot-BMW (05-Feb-2006).

INSIZ: Maximum size of webpages indexed by MSN/Google/Yahoo! ("100-kb limit"): Max Page-size (28-Apr-2006).

^ http://www.w3.org/History/19921103-hypertext/hypertext/DataSources/WWW/Servers.html

^ http://home.mcom.com/home/whatsnew/whats_new_0294.html

^ "Internet History - Search Engines" (from Search Engine Watch), Universiteit Leiden, Netherlands, September 2001, web: LeidenU-Archie.

^ Oscar Nierstrasz (2 September 1993). "Searchable Catalog of WWW Resources (experimental)" (html). http://groups.google.com/group/comp.infosystems.www/browse_thread/thread/2176526a36dc8bd3/2718fd17812937ac?hl=en&lnk=gst&q=Oscar+Nierstrasz#2718fd17812937ac.

^ Archive of NCSA what's new in December 1993 page

^ Yahoo! And Netscape Ink International Distribution Deal, http://files.shareholder.com/downloads/YHOO/701084386x0x27155/9a3b5ed8-9e84-4cba-a1e5-77a3dc606566/YHOO_News_1997_7_8_General.pdf

^ Browser Deals Push Netscape Stock Up 7.8%, Los Angeles Times, 1 April 1996, http://articles.latimes.com/1996-04-01/business/fi-53780_1_netscape-home

^ Gandal, Neil (2001). "The dynamics of competition in the internet search engine market". International Journal of Industrial Organization 19 (7): 11031117. doi:10.1016/S0167-7187(01)00065-0.

^ http://marketshare.hitslink.com/search-engine-market-share.aspx?qprid=5&qpdt=1&qpct=4&qptimeframe=M&qpsp=103&qpnp=25

^ http://en-us.nielsen.com/rankings/insights/rankings/internet

^ http://risetothetop.techwyse.com/internet-marketing/search-engine-market-share-july-2009/

^ "Unknown letter from Descartes found"

^ (Dutch)" Hoe Descartes in 1641 op andere gedachten kwam - Onbekende brief van Franse filosoof gevonden"

Further reading

For a more detailed history of early search engines, see Search Engine Birthdays (from Search Engine Watch), Chris Sherman, September 2003.

Steve Lawrence; C. Lee Giles (1999). "Accessibility of information on the web". Nature 400: 107. doi:10.1038/21987.

Bing Liu (2007), Web Data Mining: Exploring Hyperlinks, Contents and Usage Data. Springer, ISBN 3540378812

Levene, Mark (2005). An Introduction to Search Engines and Web Navigation. Pearson.

Hock, Randolph (2007). The Extreme Searcher's Handbook. ISBN 978-0-910965-76-7

Javed Mostafa (February 2005). "Seeking Better Web Searches". Scientific American Magazine. http://www.sciam.com/article.cfm?articleID=0006304A-37F4-11E8-B7F483414B7F0000.

Ross, Nancy; Wolfram, Dietmar (2000). "End user searching on the Internet: An analysis of term pair topics submitted to the Excite search engine". Journal of the American Society for Information Science 51 (10): 949958. doi:10.1002/1097-4571(2000)51:103.0.CO;2-5.

Xie, M.; et al. (1998). "Quality dimensions of Internet search engines". Journal of Information Science 24 (5): 365372. doi:10.1177/016555159802400509.

External links

Search Engines at the Open Directory Project

History of Search Engines

Search Engines in every country in the world

How Stuff Works explanation of Search Engines

vde

Internet search

Types

Web search engine (List) Collaborative search engine Metasearch engine

Tools

Local search Vertical search Search engine marketing Search engine optimization Search oriented architecture Selection-based search Social search Document retrieval Text mining Web crawler Multisearch Federated search Search aggregator Index/Web indexing Focused crawler Spider trap Robots exclusion standard Distributed web crawling Web archiving Website mirroring software Web search query Voice search Human flesh search engine Natural language search engine Web query classification

Applications

Image search Video search engine Enterprise search Semantic search

Protocols and standards

Z39.50 Search/Retrieve Web Service Search/Retrieve via URL OpenSearch Representational State Transfer Website Parse Template Wide Area Information Servers

See also

Search engine Desktop search

Categories: Information retrieval | Internet search engines | Internet terminologyHidden categories: Wikipedia semi-protected pages | All articles with unsourced statements | Articles with unsourced statements from February 2008 | Articles needing additional references from November 2007 | All articles needing additional references | Articles needing additional references from December 2009 | Wikipedia references cleanup from September 2009

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