Web search engine

A web search engine or Internet search engine is a software system that is designed to carry out web search (Internet search), which means to search the World Wide Web in a systematic way for particular information specified in a web search query. The search results are generally presented in a line of results, often referred to as search engine results pages (SERPs). The information may be a mix of web pages, images, videos, infographics, articles, research papers and other types of files. Some search engines also mine data available in databases or open directories. Unlike web directories, which are maintained only by human editors, search engines also maintain real-time information by running an algorithm on a web crawler. Internet content that is not capable of being searched by a web search engine is generally described as the deep web.

Mayflower Wikimedia Commons image search engine screenshot
The results of a search for the term "lunar eclipse" in a web-based image search engine

History

Timeline (full list)
Year Engine Current status
1993 W3Catalog Active
Aliweb Active
JumpStation Inactive
WWW Worm Inactive
1994 WebCrawler Active
Go.com Inactive, redirects to Disney
Lycos Active
Infoseek Inactive, redirects to Disney
1995 Daum Active
Magellan Inactive
Excite Active
SAPO Active
MetaCrawler Active
Yahoo! Active, Launched as a directory
AltaVista Inactive, acquired by Yahoo! in 2003, since 2013 redirects to Yahoo!
1996 Dogpile Active, Aggregator
Inktomi Inactive, acquired by Yahoo!
HotBot Active
Ask Jeeves Active (rebranded ask.com)
1997 AOL NetFind Active (rebranded AOL Search since 1999)
Northern Light Inactive
Yandex Active
1998 Google Active
Ixquick Active as Startpage.com
MSN Search Active as Bing
empas Inactive (merged with NATE)
1999 AlltheWeb Inactive (URL redirected to Yahoo!)
GenieKnows Active, rebranded Yellowee.com
Naver Active
Teoma Inactive,
2000 Baidu Active
Exalead Active
Gigablast Active
2001 Kartoo Inactive
2003 Info.com Active
Scroogle Inactive
2004 Yahoo! Search Active, Launched own web search
(see Yahoo! Directory, 1995)
A9.com Inactive
Clusty Active (as Yippy)
Mojeek Active
Sogou Active
2005 SearchMe Inactive
KidzSearch Active, Google Search
2006 Soso Inactive, merged with Sogou
Quaero Inactive
Search.com Active
ChaCha Inactive
Ask.com Active
Live Search Active as Bing, rebranded MSN Search
2007 wikiseek Inactive
Sproose Inactive
Wikia Search Inactive
Blackle.com Active, Google Search
2008 Powerset Inactive (redirects to Bing)
Picollator Inactive
Viewzi Inactive
Boogami Inactive
LeapFish Inactive
Forestle Inactive (redirects to Ecosia)
DuckDuckGo Active
2009 Bing Active, rebranded Live Search
Yebol Inactive
Mugurdy Inactive due to a lack of funding
Scout (Goby) Active
NATE Active
Ecosia Active
Startpage.com Active, sister engine of Ixquick
2010 Blekko Inactive, sold to IBM
Cuil Inactive
Yandex (English) Active
Parsijoo Active
2011 YaCy Active, P2P web search engine
2012 Volunia Inactive
2013 Qwant Active
2014 Egerin Active, Kurdish / Sorani search engine
Swisscows Active
2015 Yooz Active
Cliqz Active, Browser integrated search engine
2016 Search Encrypt Active
Kiddle Active, Google Search

Internet search engines themselves predate the debut of the Web in December 1990. The Who is user search dates back to 1982[1] and the Knowbot Information Service multi-network user search was first implemented in 1989.[2] The first well documented search engine that searched content files, namely FTP files was Archie, which debuted on 10 September 1990.[3]

Prior to September 1993, the World Wide Web was entirely indexed by hand. There was a list of webservers edited by Tim Berners-Lee and hosted on the CERN webserver. One snapshot of the list in 1992 remains,[4] but as more and more web servers went online the central list could no longer keep up. On the NCSA site, new servers were announced under the title "What's New!"[5]

The first tool used for searching content (as opposed to users) on the Internet was Archie.[6] The name stands for "archive" without the "v". It was created by Alan Emtage, Bill Heelan and J. Peter Deutsch, computer science students at McGill University in Montreal, Quebec, Canada. 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 Search Engine did not index the contents of these sites since the amount of data was so limited it could be readily searched manually.

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 Search Engine" 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 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 periodically mirrored these pages and rewrote them into a standard format. This formed the basis for W3Catalog, the web's first primitive search engine, released on September 2, 1993.[7]

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 (created in December 1993[8] by Jonathon Fletcher) 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 it ran on, its indexing and hence searching were limited to the titles and headings found in the web pages the crawler encountered.

One of the first "all text" crawler-based search engines was WebCrawler, which came out in 1994. Unlike its predecessors, it allowed users to search for any word in any webpage, which has become the standard for all major search engines since. It was also the search engine that was 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 its 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 as the featured search engine on Netscape's web browser. There was so much interest that instead Netscape struck deals with five of the major search engines: for $5 million a year, each search engine would be in rotation on the Netscape search engine page. The five engines were Yahoo!, Magellan, Lycos, Infoseek, and Excite.[9][10]

Google adopted the idea of selling search terms in 1998, from a small search engine company named goto.com. This move had a significant effect on the SE business, which went from struggling to one of the most profitable businesses in the Internet.[11]

Search engines were also known as some of the brightest stars in the Internet investing frenzy that occurred in the late 1990s.[12] 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, Google's search engine rose to prominence.[13] The company achieved better results for many searches with an innovation called PageRank, as was explained in the paper Anatomy of a Search Engine written by Sergey Brin and Larry Page, the later founders of Google.[14] 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. In fact, Google search engine became so popular that spoof engines emerged such as Mystery Seeker.

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. For a short time in 1999, MSN Search used results from AltaVista 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.

As of 2018, active search engine crawlers include that of Google, Bing, Gigablast, Mojeek, Baidu and Yandex.

Approach

A search engine maintains the following processes in near real time:

  1. Web crawling
  2. Indexing
  3. Searching[15]

Web search engines get their information by web crawling from site to site. The "spider" checks for the standard filename robots.txt, addressed to it, before sending certain information back to be indexed depending on many factors, such as the titles, page content, JavaScript, Cascading Style Sheets (CSS), headings, as evidenced by the standard HTML markup of the informational content, or its metadata in HTML meta tags. "[N]o web crawler may actually crawl the entire reachable web. Due to infinite websites, spider traps, spam, and other exigencies of the real web, crawlers instead apply a crawl policy to determine when the crawling of a site should be deemed sufficient. Some sites are crawled exhaustively, while others are crawled only partially".[16]

Indexing means associating words and other definable tokens found on web pages to their domain names and HTML-based fields. The associations are made in a public database, made available for web search queries. A query from a user can be a single word. The index helps find information relating to the query as quickly as possible.[15] Some of the techniques for indexing, and caching are trade secrets, whereas web crawling is a straightforward process of visiting all sites on a systematic basis.

Between visits by the spider, the cached version of page (some or all the content needed to render it) stored in the search engine working memory is quickly sent to an inquirer. If a visit is overdue, the search engine can just act as a web proxy instead. In this case the page may differ from the search terms indexed.[15] The cached page holds the appearance of the version whose words were indexed, so a cached version of a page can be useful to the web site when the actual page has been lost, but this problem is also considered a mild form of linkrot.

WebCrawlerArchitecture
High-level architecture of a standard Web crawler

Typically when a user enters a query into a search engine it is a few keywords.[17] The index already has the names of the sites containing the keywords, and these are instantly obtained from the index. The real processing load is in generating the web pages that are the search results list: Every page in the entire list must be weighted according to information in the indexes.[15] Then the top search result item requires the lookup, reconstruction, and markup of the snippets showing the context of the keywords matched. These are only part of the processing each search results web page requires, and further pages (next to the top) require more of this post processing.

Beyond simple keyword lookups, search engines offer their own GUI- or command-driven operators and search parameters to refine the search results. These provide the necessary controls for the user engaged in the feedback loop users create by filtering and weighting while refining the search results, given the initial pages of the first search results. For example, from 2007 the Google.com search engine has allowed one to filter by date by clicking "Show search tools" in the leftmost column of the initial search results page, and then selecting the desired date range.[18] It's also possible to weight by date because each page has a modification time. Most search engines support the use of the boolean operators AND, OR and NOT to help end users refine 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.[15] 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.[19] A site like this would be ask.com.[20]

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.[15] 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 first 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 thus some of them allow advertisers to have their listings ranked higher in search results for a fee. Search engines that do not accept money for their search 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.[21]

Market share

Google is the world's most popular search engine, with a market share of 92.86 percent as of February, 2019.[22]

The world's most popular search engines are:

East Asia and Russia

In some East Asian countries and Russia, Google is not the most popular search engine.

In Russia, Yandex commands a marketshare of 61.9 percent, compared to Google's 28.3 percent.[23] In China, Baidu is the most popular search engine.[24] South Korea's homegrown search portal, Naver, is used for 70 percent of online searches in the country.[25] Yahoo! Japan and Yahoo! Taiwan are the most popular avenues for Internet searches in Japan and Taiwan, respectively.[26]

Europe

Most countries' markets in Western Europe are dominated by Google, except for Czech Republic, where Seznam is a strong competitor.[27]

Search engine bias

Although search engines are programmed to rank websites based on some combination of their popularity and relevancy, empirical studies indicate various political, economic, and social biases in the information they provide[28][29] and the underlying assumptions about the technology.[30] These biases can be a direct result of economic and commercial processes (e.g., companies that advertise with a search engine can become also more popular in its organic search results), and political processes (e.g., the removal of search results to comply with local laws).[31] For example, Google will not surface certain neo-Nazi websites in France and Germany, where Holocaust denial is illegal.

Biases can also be a result of social processes, as search engine algorithms are frequently designed to exclude non-normative viewpoints in favor of more "popular" results.[32] Indexing algorithms of major search engines skew towards coverage of U.S.-based sites, rather than websites from non-U.S. countries.[29]

Google Bombing is one example of an attempt to manipulate search results for political, social or commercial reasons.

Several scholars have studied the cultural changes triggered by search engines,[33] and the representation of certain controversial topics in their results, such as terrorism in Ireland,[34] climate change denial,[35] and conspiracy theories.[36]

Customized results and filter bubbles

Many search engines such as Google and Bing provide customized results based on the user's activity history. This leads to an effect that has been called a filter bubble. The term describes a phenomenon in which websites use algorithms to selectively guess what information a user would like to see, based on information about the user (such as location, past click behaviour and search history). As a result, websites tend to show only information that agrees with the user's past viewpoint. This puts the user in a state of intellectual isolation without contrary information. Prime examples are Google's personalized search results and Facebook's personalized news stream. According to Eli Pariser, who coined the term, users get less exposure to conflicting viewpoints and are isolated intellectually in their own informational bubble. Pariser related an example in which one user searched Google for "BP" and got investment news about British Petroleum while another searcher got information about the Deepwater Horizon oil spill and that the two search results pages were "strikingly different".[37][38][39] The bubble effect may have negative implications for civic discourse, according to Pariser.[40] Since this problem has been identified, competing search engines have emerged that seek to avoid this problem by not tracking or "bubbling" users, such as DuckDuckGo. Other scholars do not share Pariser's view, finding the evidence in support of his thesis unconvincing.[41]

Christian, Islamic and Jewish search engines

The global growth of the Internet and electronic media in the Arab and Muslim World during the last decade has encouraged Islamic adherents in the Middle East and Asian sub-continent, to attempt their own search engines, their own filtered search portals that would enable users to perform safe searches. More than usual safe search filters, these Islamic web portals categorizing websites into being either "halal" or "haram", based on modern, expert, interpretation of the "Law of Islam". ImHalal came online in September 2011. Halalgoogling came online in July 2013. These use haram filters on the collections from Google and Bing (and others).[42]

While lack of investment and slow pace in technologies in the Muslim World has hindered progress and thwarted success of an Islamic search engine, targeting as the main consumers Islamic adherents, projects like Muxlim, a Muslim lifestyle site, did receive millions of dollars from investors like Rite Internet Ventures, and it also faltered. Other religion-oriented search engines are Jewogle, the Jewish version of Google,[43] and SeekFind.org, which is Christian. SeekFind filters sites that attack or degrade their faith.[44]

Search engine submission

Web search engine submission is a process in which a webmaster submits a website directly to a search engine. While search engine submission is sometimes presented as a way to promote a website, it generally is not necessary because the major search engines use web crawlers, that will eventually find most web sites on the Internet without assistance. They can either submit one web page at a time, or they can submit the entire site using a sitemap, but it is normally only necessary to submit the home page of a web site as search engines are able to crawl a well designed website. There are two remaining reasons to submit a web site or web page to a search engine: to add an entirely new web site without waiting for a search engine to discover it, and to have a web site's record updated after a substantial redesign.

Some search engine submission software not only submits websites to multiple search engines, but also add links to websites from their own pages. This could appear helpful in increasing a website's ranking, because external links are one of the most important factors determining a website's ranking. However, John Mueller of Google has stated that this "can lead to a tremendous number of unnatural links for your site" with a negative impact on site ranking.[45]

See also

References

  1. ^ "RFC 812 - NICNAME/WHOIS". ietf.org.
  2. ^ "Knowbot programming: System support for mobile agents". cnri.reston.va.us.
  3. ^ Deutsch, Peter (September 11, 1990). "[next] An Internet archive server server (was about Lisp)". groups.google.com. Retrieved 2017-12-29.
  4. ^ "World-Wide Web Servers". W3.org. Retrieved 2012-05-14.
  5. ^ "What's New! February 1994". Home.mcom.com. Retrieved 2012-05-14.
  6. ^ "Internet History - Search Engines" (from Search Engine Watch), Universiteit Leiden, Netherlands, September 2001, web: LeidenU-Archie.
  7. ^ Oscar Nierstrasz (2 September 1993). "Searchable Catalog of WWW Resources (experimental)".
  8. ^ "Archive of NCSA what's new in December 1993 page". 2001-06-20. Archived from the original on 2001-06-20. Retrieved 2012-05-14.
  9. ^ "Yahoo! And Netscape Ink International Distribution Deal" (PDF)
  10. ^ "Browser Deals Push Netscape Stock Up 7.8%". Los Angeles Times. 1 April 1996
  11. ^ Pursel, Bart. "Search Engines". Penn State Pressbooks. Retrieved February 20, 2018.
  12. ^ Gandal, Neil (2001). "The dynamics of competition in the internet search engine market". International Journal of Industrial Organization. 19 (7): 1103–1117. doi:10.1016/S0167-7187(01)00065-0.
  13. ^ "Our History in depth". W3.org. Retrieved 2012-10-31.
  14. ^ Brin, Sergey; Page, Larry. "The Anatomy of a Large-Scale Hypertextual Web Search Engine" (PDF).
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  16. ^ Dasgupta, Anirban; Ghosh, Arpita; Kumar, Ravi; Olston, Christopher; Pandey, Sandeep; and Tomkins, Andrew. The Discoverability of the Web. http://www.arpitaghosh.com/papers/discoverability.pdf
  17. ^ Jansen, B. J., Spink, A., and Saracevic, T. 2000. Real life, real users, and real needs: A study and analysis of user queries on the web. Information Processing & Management. 36(2), 207-227.
  18. ^ Chitu, Alex (August 30, 2007). "Easy Way to Find Recent Web Pages". Google Operating System. Retrieved 22 February 2015.
  19. ^ "Versatile question answering systems: seeing in synthesis", Mittal et al., IJIIDS, 5(2), 119-142, 2011.
  20. ^ http://www.ask.com. Retrieved 10 September 2015.
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  25. ^ "How Naver Hurts Companies' Productivity". The Wall Street Journal. 2014-05-21. Retrieved 2014-06-04.
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  27. ^ Seznam Takes on Google in the Czech Republic. Doz.
  28. ^ Segev, El (2010). Google and the Digital Divide: The Biases of Online Knowledge, Oxford: Chandos Publishing.
  29. ^ a b Vaughan, Liwen; Mike Thelwall (2004). "Search engine coverage bias: evidence and possible causes". Information Processing & Management. 40 (4): 693–707. CiteSeerX 10.1.1.65.5130. doi:10.1016/S0306-4573(03)00063-3.
  30. ^ Jansen, B. J. and Rieh, S. (2010) The Seventeen Theoretical Constructs of Information Searching and Information Retrieval. Journal of the American Society for Information Sciences and Technology. 61(8), 1517-1534.
  31. ^ Berkman Center for Internet & Society (2002), "Replacement of Google with Alternative Search Systems in China: Documentation and Screen Shots", Harvard Law School.
  32. ^ Introna, Lucas; Helen Nissenbaum (2000). "Shaping the Web: Why the Politics of Search Engines Matters". The Information Society: An International Journal. 16 (3): 169–185. CiteSeerX 10.1.1.24.8051. doi:10.1080/01972240050133634.
  33. ^ Hillis, Ken; Petit, Michael; Jarrett, Kylie (2012-10-12). Google and the Culture of Search. Routledge. ISBN 9781136933066.
  34. ^ Reilly, P. (2008-01-01). Spink, Prof Dr Amanda; Zimmer, Michael (eds.). 'Googling' Terrorists: Are Northern Irish Terrorists Visible on Internet Search Engines?. Information Science and Knowledge Management. 14. Springer Berlin Heidelberg. pp. 151–175. doi:10.1007/978-3-540-75829-7_10. ISBN 978-3-540-75828-0.
  35. ^ Hiroko Tabuchi, "How Climate Change Deniers Rise to the Top in Google Searches", The New York Times, Dec. 29, 2017. Retrieved November 14, 2018.
  36. ^ Ballatore, A (2015). "Google chemtrails: A methodology to analyze topic representation in search engines". First Monday. 20 (7). doi:10.5210/fm.v20i7.5597.
  37. ^ Parramore, Lynn (10 October 2010). "The Filter Bubble". The Atlantic. Retrieved 2011-04-20. Since Dec. 4, 2009, Google has been personalized for everyone. So when I had two friends this spring Google "BP," one of them got a set of links that was about investment opportunities in BP. The other one got information about the oil spill....
  38. ^ Weisberg, Jacob (10 June 2011). "Bubble Trouble: Is Web personalization turning us into solipsistic twits?". Slate. Retrieved 2011-08-15.
  39. ^ Gross, Doug (May 19, 2011). "What the Internet is hiding from you". CNN. Retrieved 2011-08-15. I had friends Google BP when the oil spill was happening. These are two women who were quite similar in a lot of ways. One got a lot of results about the environmental consequences of what was happening and the spill. The other one just got investment information and nothing about the spill at all.
  40. ^ Zhang, Yuan Cao; Séaghdha, Diarmuid Ó; Quercia, Daniele; Jambor, Tamas (February 2012). "Auralist: Introducing Serendipity into Music Recommendation" (PDF). ACM Wsdm.
  41. ^ O'Hara, K. (2014-07-01). "In Worship of an Echo". IEEE Internet Computing. 18 (4): 79–83. doi:10.1109/MIC.2014.71. ISSN 1089-7801.
  42. ^ "New Islam-approved search engine for Muslims". News.msn.com. Retrieved 2013-07-11.
  43. ^ "Jewogle - FAQ".
  44. ^ "Halalgoogling: Muslims Get Their Own "sin free" Google; Should Christians Have Christian Google? - Christian Blog". Christian Blog. 2013-07-25.
  45. ^ Schwartz, Barry (2012-10-29). "Google: Search Engine Submission Services Can Be Harmful". Search Engine Roundtable. Retrieved 2016-04-04.

Further reading

External links

User's navigation

Aliweb

ALIWEB (Archie Like Indexing for the WEB) is considered the first Web search engine, as its predecessors were either built with different purposes (the Wanderer, Gopher) or were literally just indexers (Archie, Veronica and Jughead).

First announced in November 1993 by developer Martijn Koster while working at Nexor, and presented in May 1994 at the First International Conference on the World Wide Web at CERN in Geneva, ALIWEB preceded WebCrawler by several months.ALIWEB allowed users to submit the locations of index files on their sites which enabled the search engine to include webpages and add user-written page descriptions and keywords. This empowered webmasters to define the terms that would lead users to their pages, and also avoided setting bots (e.g. the Wanderer, JumpStation) which used up bandwidth. As relatively few people submitted their sites, ALIWEB was not very widely used.

Martijn Koster, who was also instrumental in the creation of the Robots Exclusion Standard, detailed the background and objectives of ALIWEB with an overview of its functions and framework in the paper he presented at CERN.Koster is not associated with a commercial website which uses the aliweb name.

BTJunkie

BTJunkie was a BitTorrent web search engine operating between 2005 and 2012. It used a web crawler to search for torrent files from other torrent sites and store them on its database. It had nearly 4,000,000 active torrents and about 4,200 torrents added daily (compared to runner-up Torrent Portal with 1,500), making it the largest torrent site indexer on the web in 2006. During 2011, BTJunkie was the 5th most popular BitTorrent site.

Bing (search engine)

Bing is a web search engine owned and operated by Microsoft. The service has its origins in Microsoft's previous search engines: MSN Search, Windows Live Search and later Live Search. Bing provides a variety of search services, including web, video, image and map search products. It is developed using ASP.NET.

Bing, Microsoft's replacement for Live Search, was unveiled by Microsoft CEO Steve Ballmer on May 28, 2009, at the All Things Digital conference in San Diego, California, for release on June 1, 2009. Notable new features at the time included the listing of search suggestions while queries are entered and a list of related searches (called "Explore pane") based on semantic technology from Powerset, which Microsoft had acquired in 2008.In July 2009, Microsoft and Yahoo! announced a deal in which Bing would power Yahoo! Search. All Yahoo! Search global customers and partners made the transition by early 2012. The deal was altered in 2015, meaning Yahoo! was only required to use Bing for a "majority" of searches.In October 2011, Microsoft stated that they were working on new back-end search infrastructure with the goal of delivering faster and slightly more relevant search results for users. Known as "Tiger", the new index-serving technology had been incorporated into Bing globally since August that year. In May 2012, Microsoft announced another redesign of its search engine that includes "Sidebar", a social feature that searches users' social networks for information relevant to the search query.As of October 2018, Bing is the third largest search engine globally, with a query volume of 4.58%, behind Google (77%) and Baidu (14.45%). Yahoo! Search, which Bing largely powers, has 2.63%.

Gigablast

Gigablast is a free and open-source web search engine and directory. Founded in 2000, it is an independent engine and web crawler based in New Mexico, developed and maintained by Matt Wells, a former Infoseek employee and New Mexico Tech graduate.The search engine source code is written in the programming languages C and C++. It was released as open-source software under the Apache License version 2, in July 2013. In 2015, Gigablast claimed to have indexed over 12 billion web pages, and received billions of queries per month.Gigablast has provided, and provides, search results to other companies, such as Ixquick, Clusty, Zuula, Snap, Blingo, and Internet Archive.

Google Search

Google Search, also referred to as Google Web Search or simply Google, is a web search engine developed by Google LLC. It is the most used search engine on the World Wide Web across all platforms, with 92.74% market share as of October 2018, handling more than 3.5 billion searches each day.The order of search results returned by Google is based, in part, on a priority rank system called "PageRank". Google Search also provides many different options for customized search, using symbols to include, exclude, specify or require certain search behavior, and offers specialized interactive experiences, such as flight status and package tracking, weather forecasts, currency, unit and time conversions, word definitions, and more.

The main purpose of Google Search is to hunt for text in publicly accessible documents offered by web servers, as opposed to other data, such as images or data contained in databases. It was originally developed by Larry Page and Sergey Brin in 1997. In June 2011, Google introduced "Google Voice Search" to search for spoken, rather than typed, words. In May 2012, Google introduced a Knowledge Graph semantic search feature in the U.S.

Analysis of the frequency of search terms may indicate economic, social and health trends. Data about the frequency of use of search terms on Google can be openly inquired via Google Trends and have been shown to correlate with flu outbreaks and unemployment levels, and provide the information faster than traditional reporting methods and surveys. As of mid-2016, Google's search engine has begun to rely on deep neural networks.Competitors of Google include Baidu and Soso.com in China; Naver.com and Daum.net in South Korea; Yandex in Russia; Seznam.cz in the Czech Republic; Yahoo in Japan, Taiwan and the US, as well as Bing and DuckDuckGo. Some smaller search engines offer facilities not available with Google, e.g. not storing any private or tracking information.

Within the US, as of July 2018, Microsoft Sites handled 24.2 percent of all search queries in the United States. During the same period of time, Oath (formerly known as Yahoo) had a search market share of 11.5 percent. Market leader Google generated 63.2 percent of all core search queries in the United States.

HotBot

HotBot is a privately owned web search engine, currently using Bing search for its search results.

Log file

In computing, a log file is a file that records either events that occur in an operating system or other software runs, or messages between different users of a communication software. Logging is the act of keeping a log. In the simplest case, messages are written to a single log file.

A transaction log is a file (i.e., log) of the communications (i.e., transactions) between a system and the users of that system, or a data collection method that automatically captures the type, content, or time of transactions made by a person from a terminal with that system. For Web searching, a transaction log is an electronic record of interactions that have occurred during a searching episode between a Web search engine and users searching for information on that Web search engine.

Many operating systems, software frameworks and programs include a logging system. A widely used logging standard is syslog, defined in Internet Engineering Task Force (IETF) RFC 5424). The syslog standard enables a dedicated, standardized subsystem to generate, filter, record, and analyze log messages. This relieves software developers of having to design and code their own ad hoc logging systems.

Microsoft Academic

Microsoft Academic is a free public web search engine for academic publications and literature, developed by Microsoft Research. Re-launched in 2016, the tool features an entirely new data structure and search engine using semantic search technologies. It currently indexes over 375 million entities, 170 million of which are academic papers. The Academic Knowledge API offers information retrieval from the underlying database using REST endpoints for advanced research purposes.The service replaces the earlier Microsoft research project, Microsoft Academic Search, which ended development in 2012.Preliminary reviews by bibliometricians suggest the new Microsoft Academic Search is a competitor to Google Scholar, Web of Science, and Scopus for academic research purposes as well as citation analysis.

Search box

A search box, search field or search bar is a graphical control element used in computer programs, such as file managers or web browsers, and on web sites. A search box is usually a single-line text box or search icon ( which will transform into a search box on click activity) with the dedicated function of accepting user input to be searched for in a database. Search boxes on web pages are usually used to allow users to enter a query to be submitted to a Web search engine server-side script, where an index database is queried for entries that contain one or more of the user's keyword research.

Search boxes are commonly accompanied by a search button (sometimes indicated only by a magnifying glass symbol) to submit the search. However, the search button may be omitted as the user may press the enter key to submit the search, or the search may be sent automatically to present the user with real-time results.

Search engine (computing)

A search engine is an information retrieval system designed to help find information stored on a computer system. The search results are usually presented in a list and are commonly called hits. Search engines help to minimize the time required to find information and the amount of information which must be consulted, akin to other techniques for managing information overload.The most public, visible form of a search engine is a Web search engine which searches for information on the World Wide Web.

Sputnik (search engine)

Sputnik is a web search engine owned by the Russian state-owned telecommunications company Rostelecom. It markets itself as an engine geared towards "local services". At the end of the week of the launch, it was responsible for 0.01% of the search engine traffic in Russia, compared with 62% for Yandex and 28% for Google. It went through the maximum in February 2016, with 11 thousands hits (compared with 121 million hits of Yandex). In January 2017, Sputnik was the 15th most popular search engine in Russia, with 1 / 32,000 times the hits of Yandex. The experts generally consider Sputnik as a failed project and note that it only exists because of the state funding.

Swisscows

Swisscows is a web search engine launched in 2014, a project of Hulbee AG, a company based in Egnach, Switzerland.The search engine is based on semantic data recognition that give faster "answers" to queries. In addition, Swisscows does not store users' data. Swisscows also deems itself "family-friendly", with explicit results entirely omitted. The website's servers are based in underground data centers under the Swiss Alps.Swisscows uses Bing for web search, but has also built its own index for the German language edition. It also has shopping search, music search (powered by SoundCloud), and a language translator powered by Yandex.

As of 2018, there are 20 million monthly search queries, according to Hulbee CEO, Andreas Wiebe.

Vertical search

A vertical search engine is distinct from a general web search engine, in that it focuses on a specific segment of online content. They are also called specialty or topical search engines. The vertical content area may be based on topicality, media type, or genre of content. Common verticals include shopping, the automotive industry, legal information, medical information, scholarly literature, job search and travel. Examples of vertical search engines include the Library of Congress, Mocavo, Nuroa, Trulia and Yelp.

In contrast to general web search engines, which attempt to index large portions of the World Wide Web using a web crawler, vertical search engines typically use a focused crawler which attempts to index only relevant web pages to a pre-defined topic or set of topics. Some vertical search sites focus on individual verticals, while other sites include multiple vertical searches within one search engine.

Vivisimo

Vivisimo was a privately held technology company in Pittsburgh, Pennsylvania, specialising in the development of computer search engines. The company was acquired by IBM in May 2012 and is now branded as IBM Watson Explorer, a product of the IBM Watson Group. Vivisimo's public web search engine Clusty was a metasearch engine with document clustering; it was sold to Yippy, Inc. in 2010.

Vivisimo specialized in federated search and document clustering. Clustering divides the results of a search for "cell" into groups including "biology", "battery", and "prison".

Vivisimo software supported both structured and unstructured information.

WebCrawler

WebCrawler is a web search engine, and is the oldest running search engine on the web today. For many years, it operated as a metasearch engine. WebCrawler was the first web search engine to provide full text search.

Web search query

A web search query is a query based on a specific search term that a user enters into a web search engine to satisfy his or her information needs. Web search queries are distinctive in that they are often plain text or hypertext with optional search-directives (such as "and"/"or" with "-" to exclude). They vary greatly from standard query languages, which are governed by strict syntax rules as command languages with keyword or positional parameters.

Wikia Search

Wikia Search was a short-lived free and open-source web search engine launched by Wikia, a for-profit wiki-hosting company founded in late 2004 by Jimmy Wales and Angela Beesley.Wikia Search followed other experiments by Wikia into search engine technology and officially launched as a "public alpha" on January 7, 2008. The roll-out version of the search interface was widely criticized by reviewers in mainstream media.

Yandex Search

Yandex Search is a web search engine owned by Russian corporation Yandex. It is the core product of Yandex. In January 2015 Yandex Search generated 51.2% of all search traffic in Russia according to LiveInternet.

Types
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See also
Web search engines
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