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Find/Seeking the Information You Want on the Internet:
The find program is a directory search utility on Unix-like platforms. It searches through one or more directory trees of a filesystem, locating files based on some user-specified criteria. By default, find returns all files below the current working directory. Further, find allows the user to specify an action to be taken on each matched file. Thus, it is an extremely powerful program for applying actions to many files. It also supports regex matching.
The find program is no longer preferred for searching for files by name in the entire filesystem. Instead, the locate programs, which use a database of indexed files, is more efficient.
Searching the Internet:
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 called "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 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.
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. Another very early search engine, Aliweb, also appeared in 1993, and still runs today. JumpStation (released in early 1994) used a crawler to find web pages for searching, but search was limited to the title of web pages only. 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 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) was launched, 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. 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.
Search engines were also known as some of the brightest stars in the Internet investing frenzy that occurred in the late 1990's. 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. 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 using 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 (since re-branded Live 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).
As of late 2007, Google was by far the most popular Web search engine worldwide. A number of country-specific search engine companies have become prominent; for example Baidu is the most popular search engine in the People's Republic of China and WikiPedia.
A Search Engine Operates in the Following Order:
1. Web Crawling - (also known as a web spider or web robot or - especially in the FOAF community - web scutter) is a program or automated script which browses the World Wide Web in a methodical, automated manner. Other less frequently used names for web crawlers are ants, automatic indexers, bots, and worms.
This process is called web crawling or spidering. Many sites, in particular search engines, use spidering as a means of providing up-to-date data. Web crawlers are mainly used to create a copy of all the visited pages for later processing by a search engine that will index the downloaded pages to provide fast searches. Crawlers can also be used for automating maintenance tasks on a website, such as checking links or validating HTML code. Also, crawlers can be used to gather specific types of information from Web pages, such as harvesting e-mail addresses (usually for spam).
A web crawler is one type of bot, or software agent. In general, it starts with a list of URLs to visit, called the seeds. As the crawler visits these URLs, it identifies all the hyperlinks in the page and adds them to the list of URLs to visit, called the crawl frontier. URLs from the frontier are recursively visited according to a set of policies.
2. Indexing - Search engine indexing collects, parses, and stores data to facilitate fast and accurate information retrieval. Index design incorporates interdisciplinary concepts from linguistics, cognitive psychology, mathematics, informatics, physics and computer science. An alternate name for the process in the context of search engines designed to find web pages on the Internet is Web indexing.
Popular engines focus on the full-text indexing of online, natural language documents; media types such as video and audio and graphics are also searchable.
Meta search engines reuse the indices of other services and do not store a local index, whereas cache-based search engines permanently store the index along with the corpus. Unlike full-text indices, partial-text services restrict the depth indexed to reduce index size. Larger services typically perform indexing at a predetermined time interval due to the required time and processing costs, while agent-based search engines index in real time.
3. Searching - A web search query is a query that a user enters into web search engine to satisfy his or her information needs. Web search queries are distinctive in that they are unstructured and often ambiguous; they vary greatly from standard query languages which are governed by strict syntax rules.
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 (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 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 (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. 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.
The usefulness of a search engine depends on the relevance of the result set it gives back. While there may be millions of webpages 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 every time someone clicks on one of these ads.
The vast majority of search engines are run by private companies using proprietary algorithms and closed databases, though some are open source.
Geospatially-Enabled Web Search Engines:
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 (such as a polygonal boundary for a municipality). 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.
Social Web Search:
A social search engine is a type of search engine that determines the relevance of search results by considering the interactions or contributions of users. Example forms of user input include social bookmarking or direct interaction with the search results such as promoting or demoting results the user feels are more or less relevant to their query. When applied to web search this user-based approach to relevance is in contrast to established algorithmic or machine-based approaches where relevance is determined by analyzing the text of each document or the link structure of the documents (ex: the basis of PageRank). Social search takes many forms, ranging from simple shared bookmarks or tagging of content with descriptive labels to more sophisticated approaches that combine human intelligence with computer algorithms.
The Problems with Search Engines:
The usage of Search Engines, or Directories Used to Search the Internet, is that there is too much data to asctually find the thing one looks for on the Internet. Over time, we tend to use a Directory less as our brain becomes familiar with the information source of our interest that led us to Search in the first place.
A newer type of information gathering web destination location is actually evolving that will "Find" the subject deliminated information one is really seeking on the Internet. Surveys have shown web surfers tend to not go beyong the first couple of pages of links found by using the Search Engines. Therefore, the information needed to make a decision may be overlooked or not even found due to the massive amount of informational links, repetitive web site links, "landing sites" that have nothing in content except advertising links, or a connection that loads the surfer's computer with undesirable SPAM.
In an article recently posted on InfoWorld called the "Demise of Google™", the author submits that "Niche, vertical, boutique -- call them what you will -- Search Engines" will ultimately erode the general search engine – Google, just as niche, specific interest magazines replaced the general interest magazines of the 50’s and 60’s. Radio replaced newspapers as the place people get information; TV replaced radio, and the Internet is replacing ALL of the other forms of media today where Consumers get the Information they want to make Transactional Decisions!
The author compares a search done with a "niche" search engine and Google™, and the results are obvious - why start your search with all the information on the Internet, when you can start with a specific pre-defined "niche."
The author states: "There are numerous examples of vertical search engines, such as WebMD, Travelocity, Orbitz, Petfinder, Kayak, Monster, and CareerBuilder."
Obviously "niche/targeted" is better than "general" (it's the very foundation of Google's Adsense) - MORE targeted, therefore MORE effective and MORE efficient, therefore MORE sales.
The question is: After thousands of "niche, vertical, boutique" whatever sites come out with IDENTICAL content and IDENTICAL claims of superiority - who will ultimately dominate?
The winner will be the one system that consumers perceive to be MORE authentic, and MORE credible than the others.
WikipediA has proved this concept DOES REALLY work! WikipediA is now the #3 Search Engine in the world behind Google™ and Yahoo®; who alone are worth over $200 Billion Dollars! These TWO Search Engines are now worth more that all of the car companies combined!
WikiPediA™ is Academic/Educational based.
Information Brands like Noun+Pedia™ are Consumer based brands, and the growing trend found on the Internet. The Pedia™ brands can effectively compete in each "niche" and only the Pedia™ brands create the overwhelming perception of MORE authenticity and MORE credibility.
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