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this is very much how the Web is set up. Tree searches, then, are more useful when con-
ducting searches on the Web, although they are not the only searches that can be successful.
SQL search:
One of the difficulties with a tree search is that it’s conducted in a hierar-
chical manner, meaning it’s conducted from one point to another, according to the
ranking of the data being searched. A SQL (pronounced See-Quel) search allows data
to be searched in a non-hierarchical manner, which means that data can be searched
from any subset of data.
Informed search:
An informed search algorithm looks for a specific answer to a specific
problem in a tree-like data set. The informed search, despite its name, is not always the
best choice for web searches because of the general nature of the answers being sought.
Instead, informed search is better used for specific queries in specific data sets.
Adversarial search:
An adversarial search algorithm looks for all possible solutions to a
problem, much like finding all the possible solutions in a game. This algorithm is difficult
to use with web searches, because the number of possible solutions to a word or phrase
search is nearly infinite on the Web.
Constraint satisfaction search:
When you think of searching the Web for a word or
phrase, the constraint satisfaction search algorithm is most likely to satisfy your desire to
find something. In this type of search algorithm, the solution is discovered by meeting a
set of constraints, and the data set can be searched in a variety of different ways that do not
have to be linear. Constraint satisfaction searches can be very useful for searching the Web.
These are only a few of the various types of search algorithms that are used when creating search
engines. And very often, more than one type of search algorithm is used, or as happens in most
cases, some proprietary search algorithm is created. The key to maximizing your search engine
results is to understand a little about how each search engine you’re targeting works. Only when
you understand this can you know how to maximize your exposure to meet the search require-
ments for that search engine.
Retrieval and ranking
For a web search engine, the retrieval of data is a combination activity of the crawler (or spider or
robot), the database, and the search algorithm. Those three elements work in concert to retrieve the
word or phrase that a user enters into the search engine’s user interface. And as noted earlier, how
that works can be a proprietary combination of technologies, theories, and coding whizbangery.
The really tricky part comes in the results ranking. Ranking is also what you’ll spend the most time
and effort trying to affect. Your ranking in a search engine determines how often people see your page,
which affects everything from revenue to your advertising budget. Unfortunately, how a search engine
ranks your page or pages is a tough science to pin down.
The most that you can hope for, in most cases, is to make an educated guess as to how a search
engine ranks its results, and then try to tailor your page to meet those results. But keep in mind
that, although retrieval and ranking are listed as separate subjects here, they’re actually part of the
search algorithm. The separation is to help you better understand how search engines work.
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Search Engine Basics
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