General search engines Open source search engines Metasearch engines Regional search engines People search engines E-mail–based search engines Visual search engines Answer-based search engines Google-based search engines Yahoo!-based search engines Windows-Live–based search engines Job search engines
Google, Windows Live, Yahoo! Search DataParkSearch, Namazu, Xapian Dogpile, Excite, Hotbot, Mamma, Sidestep Baidu (China), Naver (Korea), Rediff (India) Chacha, Zoominfo TEK Kartoo, Grokker Answers.com, Lycos IQ, Yahoo! Answers AOL Search, Netscape AltaVista, GoodSearch A9.com (Amazon), Lycos, Alexa Internet Hotjobs.com, Monster.com, Craigslist.org,
Blog search engines News search engines Multimedia search engines Code search engines Bit Torrent search engines Accountancy search engines Medical search engines Property search engines Business search engines Comparison shopping search engines Geographic search engines Social search engines Desktop search engines
Jobster.com Bloglines, IceRocket, Pubsub.com Google News, Yahoo! News, Topix.net Podscope, Picsearch Krugle, Koders Bit Torrent, Mininova IFACnet WebMD, Entrez Zillow, Home.co.uk Thomasnet, Business.com Froogle, MySimon, PriceGrabber, Shopzilla Google Maps, Map Quest, Yahoo! Maps Google Co-op, Rollyo, Wink Ask.com, Google desktop, Copernic, Hotbot,
Video search engine
XI Enterprise Mamma.com
Categories of Search Engine
Part 4: Other EC Models and Applications
Online File W8.1 (continued)
In November 2004, Microsoft released its test version of MSN Search (now Windows Live), its primary artillery in the search wars. MSN Search seeks to fulfill the battle cry its CEO Bill Gates issued earlier in 2004: “We took an approach [ignoring the Web search market] that I now realize was wrong, [but] we will catch them” (Markoff 2004c). Perhaps more significant, Microsoft includes comprehensive Web and desktop search capabilities in Vista, its Windows operating system.
Google also is facing competition from smaller companies that are trying to create the next “great leap forward” in Web search technology (Roush 2004). For example:
Mooter (moote .com) makes searches more personal by recording which links get clicked and adjusting the ranking of Web sites in subsequent searches based on these preferences.
Clusty (clusty.com) organizes search results into folders, or “clusters,” by grouping similar items together based on textual and linguistic similarity. For example, a search on “George Bush” produces clusters such as “White House,” “election,” “quotes,” and “Iraq,” and each cluster contains a number of search results.
Snap (snap.com) uses click-stream information (e.g., what sites Web users visit, how long they stay) to rank Web search results as well as sorting the results based on various criteria.