Meta-Tags sind (versteckte) HTML-Elemente auf einer Webseite, welche Metadaten ueber das betreffende Dokument enthalten. Es existieren verschiedene Metadaten-Schemata, teils von Institutionen oder Gremien erarbeitet (zum Beispiel Dublin Core), teils aber auch wild gewachsene Arten wie Eintraege der Erzeuger-Software (zum Beispiel Hersteller und Version). Die wenigsten dieser Metainformationen werden von User Agents (zum Beispiel Browsern oder Suchrobotern) interpretiert, sodass sie dem Leser einer Webseite fuer gewoehnlich verborgen bleiben. Die Beachtung durch den User Agent ist, wie bei allen HTML-Elementen, von den Faehigkeiten und der Konfiguration desselben anhaengig. Meta-Tags sollen vor allem die Durchsuchbarkeit des World Wide Webs bzw. einer einzelnen Webpraesenz verbessern. Ausserdem lassen sich mithilfe von Meta-Tags spezielle Anweisungen zur Steuerung der Suchroboter von Suchmaschinen Weblog,Suchmaschinen notieren. Einst galten Meta-Tags als Geheimwaffe, um bei einer Suchmaschine oder einem Webkatalog moeglichst weit oben gelistet zu werden. Meta-Tags wurden daher lange missbraucht, um irrefuehrende Schlagwoerter anzugeben. Mittlerweile legen die Suchmaschinen wieder mehr Wert auf den eigentlichen Textinhalt einer Webseite, den auch der Leser im Browser wahrnimmt, und ignorieren Meta-Angaben weitestgehend bzw. lassen diese nicht mehr in das Ranking der Seite einfliessen. Die Meta-Tags stehen im Kopf-Bereich eines HTML-Dokuments, also im head-Element. Im Web finden sich unzaehlige „Meta-Tag-Generatoren“, die jedoch mit zumeist veralteten oder inflexiblen Zusammenstellungen von Meta-Angaben arbeiten und damit nur fuer wenige Anwendungsfaelle geeignet sind.opkik Meta-Tags koennen Informationen enthalten, die normalerweise in Kopfzeilen (Headern) der HTTP-Kommunikation zwischen Server und Client (z. B. einem Webbrowser) uebertragen werden. Urspruenglich war es so gedacht, dass diese Angaben vom Webserver ausgelesen und umgesetzt werden. Dies ist aber in den meisten Faellen nicht der Fall und somit liegt es am Client, diese Angaben wie HTTP-Header zu behandeln. Daneben haben sich – beguenstigt durch den „Browserkrieg“ in den 90er Jahren – auch einige solche Meta-Tags durchgesetzt, die nie als HTTP-Kopfzeile vorgesehen waren. Nicht nur Suchmaschinen nutzen Metadaten, auch ein Webkatalog, Verzeichnis oder eine Meta Suchmaschine wie Metager arbeitet mit den Metainformationen und verfuegt ueber solche. Ein Suchmaschinen Robot kann somit schnell den eigentlichen Inhalt der Seite vordiagnostizieren und trifft die thematische Einstufung der Seite besser. Bei Suchmaschinen Marketing wird oft mit Metadaten gearbeitet, bevor es an die weiteren Optimierungs Schritte geht. Somit kann auch ein einfacher smilie oder eine Subdomain (alternative Webadresse zur normalen Domain, auch unter Subdomains umgangssprachlich bekannt, mit Metadaten versehen werden. Als Metadaten oder Metainformationen bezeichnet man allgemein Daten, die Informationen ueber andere Daten enthalten. Bei den beschriebenen Daten handelt es sich oft um groessere Datensammlungen (Dokumente) wie Fachbuch, Datenbanken oder Dateien. So werden auch Angaben von Eigenschaften eines Objektes (beispielsweise Personennamen) als Metadaten bezeichnet. Waehrend der Begriff "Metadaten" relativ neu ist, ist sein Prinzip unter anderem jahrhundertelange bibliothekarische Praxis Unterscheidung Daten - Metadaten Eine allgemeingueltige Unterscheidung zwischen Metadaten und gewoehnlichen Daten existiert allerdings nicht, da die Bezeichnung eine Frage des Standpunkts ist: Fuer den Leser eines Buches sind der Inhalt die eigentlichen Daten, waehrend der Name des Autors oder Nummer der Auflage Metadaten sind. Fuer den Herausgeber eines Buecherkatalogs sind diese beiden Eigenschaften aber unmittelbar interessant und duerften deshalb als eigentliche Daten betrachtet werden. Versucht man zwischen Daten und Metadaten zu unterscheiden, so ist es hilfreich den "Zweck" als Begriff einzufuehren. Der Zweck bestimmt das Ergebnis; um in der Lage zu sein, einen bestimmten Zweck zu erfuellen, - ein bestimmtes Ergebnis zu erreichen, - werden Metadaten benoetigt. Das Ergebnis kann aus Daten bestehen, insbesondere koennen Metadaten in ihrer Rolle als Daten Teil des Ergebnisses sein. Beispiel: Zweck: Suche innerhalb einer Bibliothek nach allen Standorten (Karteinummern) verfuegbarer Buecher eines bestimmten Autors Metadaten: "Name des Autors" und "verfuegbar" Ergebnis: "Karteinummern" (ueber die Karteinummer sei der Standort erschliessbar)

Ein Suchmaschinen Blog, oft einfach nur SEO Blog genannt, ist eine Webseite, die periodisch neue Eintraege mit dem Schwerpunkt Suchmaschinen enthaelt. Neue Eintraege stehen an oberster Stelle, aeltere folgen in umgekehrt chronologischer Reihenfolge. Die Taetigkeit des Schreibens in einem Suchmaschinen Blog wird als Bloggen bezeichnet. Suchmaschinen Blog und Weblogs sind als Kommunikationsinstrumente von Suchmaschinen Optimierern relativ neu. Bisher werden sie vor allem von Anfaengern im Bereich der Suchmaschinen Optimierung genutzt bzw. von Suchmaschinen Optimierern als Arbeitstagebuch zur Erfassung von Erkenntnissen beim Optimieren. Mittlerweile finden sie aber auch in Deutschland weitere Verbreitung mit steigenden Interesse. Suchmaschinen Blogs treten in unterschiedlichen Formen auf und koennen unterschiedliche Funktion haben. Charakteristisch fuer SEO Blogs ist, im Gegensatz zu anderen, im Marketing genutzten Weblogs, dass sie sich hauptsaechlich mit dem Thema Suchmaschinen Marketing und Suchmaschinen News, sowie deren Veraenderungen beschaeftigen. Ein Suchmaschinen Blog kann sowohl in der internen als auch in der externen Kommunikation eingesetzt werden. Liste von Suchmaschinen Blogs: Suchmaschinen Blog seekXL SEO Blog at web Blog KSO Blog

A search engine or search service is a program designed to help find information stored on a computer system such as the World Wide Web, inside a corporate or proprietary network or a personal computer. The search engine allows one to ask for content meeting specific criteria (typically those containing a given word or phrase) and retrieves a list of references that match those criteria. Search engines use regularly updated indexes to operate quickly and efficiently. Without further qualification, search engine usually refers to a Web search engine, which searches for information on the public Web. Other kinds of search engine are enterprise search engines, which search on intranets, personal search engines, which search individual personal computers, and mobile search engines. However, while different selection and relevance criteria may apply in different environments, the user will probably perceive little difference between operations in these. Some search engines also mine data available in newsgroups, large databases, or open directories like DMOZ.org. Unlike Web directories, which are maintained by human editors, search engines operate algorithmically. Most Web sites which call themselves search engines are actually front ends to search engines owned by other companies. The very first tool used for searching on the Internet was Archie. (The name stands for "archive" without the "v", not the character from the 'Archie' comic book series). 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 filenames. While Archie indexed computer files, Gopher indexed plain text documents. Webkatalog Gopher was created in 1991 by Mark McCahill at the University of Minnesota. (The program was named after the school's mascot). Because these were text files, most of the Gopher sites became Web sites after the creation of the World Wide Web. Two other programs,Veronica and Jughead, searched the files 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 various Gopher servers. The first Web search engine was Wandex (without the topics), a now-defunct index collected by the World Wide Web Wanderer, a web crawler developed by Matthew Gray at MIT in 1993. Another very early search engine, Aliweb, also appeared in 1993, and still runs today. The first "full text" crawler-based search engine was WebCrawler, which came out in 1994. Unlike its predecessors, it let users search for any word in any web page, which became 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) came out, and became a major commercial endeavor. Soon after, many search engines appeared and vied for popularity. These included Excite, Infoseek, Inktomi, Northern Light, and AltaVista. In some ways, they competed with popular directories such as Yahoo!. Later, the directories integrated or added on search engine technology for greater functionality. Suchmaschine / 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, recording 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. Before the advent of the Web, there were search engines for other protocols or uses, such as the Archie search engine for anonymous FTP sites and the Veronica search engine for the Gopher protocol. More recently search engines are also coming online which utilise XML or RSS. This allows the search engine to efficiently index data about websites without requiring a complicated crawler. The websites simply provide an xml feed which the search engine indexes. XML feeds are increasingly provided automatically by weblogs or blogs. Examples of this type of search engine are feedster, with niche examples such as LjFind Search providing search services for LiveJournal blogs. Around 2001, the Google search engine rose to prominence. Its success was based in part on the concept of link popularity and PageRank. The number of other web sites and web pages that link to a given page is taken into consideration with PageRank, on the premise that good or desirable pages are linked to more than others. The PageRank of linking pages and the number of links on these pages contribute to the PageRank of the linked page. This makes it possible for Google to order its results by how many web sites link to each found page. Google's minimalist user interface was very popular with users, and has since spawned a number of imitators. Google and most other web engines utilize not only PageRank but more than 150 criteria to determine relevancy. The algorithm "remembers" where it has been and indexes the number of cross-links and relates these into groupings. PageRank is based on citation analysis that was developed in the 1950s by Eugene Garfield at the University of Pennsylvania. Google's founders cite Garfield's work in their original paper. In this way virtual communities of webpages are found. Teoma's search technology uses a communities approach in its ranking algorithm. NEC Research Institute has worked on similar technology. Web link analysis was first developed by Dr. Jon Kleinberg and his team while working on the CLEVER project at IBM's Almaden Research Center. Google is currently the most popular search engine. In 2002, Yahoo! acquired Inktomi and in 2003, Yahoo! acquired Overture, which owned AlltheWeb and AltaVista. Despite owning its own search engine, Yahoo! initially kept using Google to provide its users with search results on its main web site Yahoo.com. However, in 2004, Yahoo! launched its own search engine based on the combined technologies of its acquisitions and providing a service that gave pre-eminence to the Web search engine over the directory. The most recent major search engine is MSN Search, owned by Microsoft, which previously relied on others for its search engine listings. In 2004 it debuted a beta version of its own results, powered by its own web crawler (called msnbot). In early 2005 it started showing its own results live. This was barely noticed by average users unaware of where results come from, but was a huge development for many webmasters, who seek inclusion in the major search engines. At the same time, Microsoft ceased using results from Inktomi, now owned by Yahoo!. The other large (self described) search engines tend to be Web portals that merely show the results from another company's search engine (as MSN Search used to do). The other "true" search engines (those that provide their own results), like Gigablast, have vastly less market presence than the big three. However, since site usage is proprietary information, it is often difficult to determine which sites are most popular. In February 2006, Ask Jeeves was rebranded as Ask.com. Games - The butler logo was removed and several new features including a redesigned home page, search tool box, maps (with walking directions and dynamic address generation) and more "Smart Answers" were added. Ask.com is now an algorithmic engine. While you can still ask questions, it operates using a relevance ranking. Ask.com utilizes the ranking algorithm that was originally developed for Teoma and its database continues to increase in size. Ask.com results pages offer several features generally unavailable elsewhere. They include page previews and "Zoom" that help the searcher narrow, expand, and select related names. These features are found on the right hand side of results pages where other engines place advertising. In 2005 it was reported that Ask.com did a great deal of work to reduce the number of paid advertisements (Games, Topics) on a results page. Web search engines work by storing information about a large number of web pages, which they retrieve from the WWW itself. These pages are retrieved by a Web crawler (sometimes also known as a spider) — 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 (for example, words are extracted from the titles, headings, or special fields called meta tags). Data about Web pages is stored in an index database for use in later queries. 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 some store every word of every page it finds, such as AltaVista. 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 Web page. 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 comes to the search engine and makes a query, typically by giving key words, the engine looks up the 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 terms AND, OR and NOT to further specify the search query. An advanced feature is proximity search, which allows you to define the distance between keywords. 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. Most Web search engines are commercial ventures supported by advertising revenue and, as a result, some employ the controversial 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 everytime someone clicks on one of these ads. The vast majority of search engines are run by private companies using proprietary algorithms and closed databases, the most popular currently being Google, MSN Search, and Yahoo! Search. However, Open source search engine technology does exist, such as ht://Dig, Nutch, Senas, Egothor, OpenFTS, DataparkSearch and many others, like Online Spiele and Online Games.