Search engines use algorithms to create a local database of information by scanning the internet, indexing all text and media on each page. They weigh the value of each page and use complex algorithms to determine relevance. The future of search is moving towards concept-based searches.
Search engines are basically computer algorithms that help users find the specific information they are looking for. Different ones work in different specific ways, but they all use the same basic principles.
The first thing search engines need to do to work is create a local, basically, Internet database. Early versions only indexed keywords and page titles, but contemporary ones index all text on each page, as well as much other data about that page’s relationship to other pages, and in some cases all or part of the media also available on the page Search engines need to index all of this information so that it can be searched for efficiently, rather than having to scour the internet every time a search query is submitted.
Search engines create these databases by periodically scanning the Internet. Early versions often required you to submit pages to be crawled, but now most pages are found by following links from other pages. What are called robots or spiders, computer programs created to index pages, go from page to page, logging all the data on the page and following each link to new pages. Different search engines update their indexes at different intervals, depending on the number of spiders they are constantly crawling and how fast these spiders are crawling, with some making their way across the Internet every day or two, and others only doing a periodic update every week or month.
As the spider traverses these pages, it records the words it finds on the pages. Takes notes on how many times each word appears, whether words are weighted in certain ways, perhaps based on size, position or HTML markup, and decides how relevant the words are based on the links coming to the page and in the overall context of the page .
Search engines therefore have to weigh the value of each page and the value of each page by the words that appear on it. This is the hardest part, but also the most important. At the simplest level it could simply track every word on the page and register that page as relevant for searches with that keyword. However, that wouldn’t help much for most users, as what you want is the most relevant page for your search query. So different engines come up with different ways of weighting importance.
The algorithms used by the various search engines are well protected, to prevent people from creating pages specifically to rank better, or at least to limit the degree to which they can do so. This difference is why different engines produce different results for the same terms. Google might determine that a page is the top result for a search term, and Ask might determine that the same page isn’t even in the top 50. This is all based only on how they evaluate inbound and outbound links, density of keywords they find important, how they rate different word rankings and any number of minor factors.
The most recent trend in search engines, and probably the future of search in general, is to move from keyword-based searches to concept-based searches. In this new form of searching, instead of limiting the search to keywords entered by the searcher, the program tries to figure out what those keywords mean, so it can suggest pages that may not include the exact word, but are still topical for the search. This is still a developing field, but so far it appears to have great potential for making searches more relevant, making the web an even easier place to find exactly what you’re looking for.
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