Search engine (computing)
Search engines discover, crawl, transform, and store information for retrieval and presentation in response to user queries.
Ranking items by relevance (from highest to lowest) reduces the time required to find the desired information.
Database size, which had been a significant marketing feature through the early 2000s, was similarly displaced by emphasis on relevancy ranking, the methods by which search engines attempt to sort the best results first.
Relevancy ranking first became a major issue c. 1996, when it became apparent that it was impractical to review full lists of results.
They are engineered to follow a multi-stage process: crawling the infinite stockpile of pages and documents to skim the figurative foam from their contents, indexing the foam/buzzwords in a sort of semi-structured form (database or something), and at last, resolving user entries/queries to return mostly relevant results and links to those skimmed documents or pages from the inventory.
These days, a continuous crawl method is employed as opposed to an incidental discovery based on a seed list.
Most search engines use sophisticated scheduling algorithms to “decide” when to revisit a particular page, to appeal to its relevance.
The speed of the web server running the page as well as resource constraints like amount of hardware or bandwidth also figure in.
Pages that are discovered by web crawls are often distributed and fed into another computer that creates a map of resources uncovered.
Another example would be the accessibility/rank of web pages containing information on Mohamed Morsi versus the very best attractions to visit in Cairo after simply entering ‘Egypt’ as a search term.
These ideas can be categorized into three main categories: rank of individual pages and nature of web site content.
Databases can be slow when solving complex queries (with multiple logical or string matching arguments).
He then proposed the idea of a virtually limitless, fast, reliable, extensible, associative memory storage and retrieval system.
Memex would also employ new retrieval techniques based on a new kind of associative indexing the basic idea of which is a provision whereby any item may be caused at will to select immediately and automatically another to create personal "trails" through linked documents.
The new procedures, that Bush anticipated facilitating information storage and retrieval would lead to the development of wholly new forms of the encyclopedia.
In 1965, Bush took part in the project INTREX of MIT, for developing technology for mechanization the processing of information for library use.
In his 1967 essay titled "Memex Revisited", he pointed out that the development of the digital computer, the transistor, the video, and other similar devices had heightened the feasibility of such mechanization, but costs would delay its achievements.
He authored a 56-page book called A Theory of Indexing which explained many of his tests, upon which search is still largely based.
In 1987, an article was published detailing the development of a character string search engine (SSE) for rapid text retrieval on a double-metal 1.6-μm n-well CMOS solid-state circuit with 217,600 transistors lain out on a 8.62x12.76-mm die area.
