Learn how to use Search Engines for better results!

Tips for better searching on the Internet...

This question was answered on July 17, 2000. Much of the information contained herein may have changed since posting.

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Search engines have the unenviable task of indexing over 2 billion (and counting) web pages to help us all find what we are looking for A recent study by the NEC Research Institute claims that search engines as a whole only index 42% of the Internet, with no single engine indexing more than 16% (www.northernlight.com) Regardless of the numbers, most search engines will return lots of irrelevant results when we ask for information Since the search engines are not very smart, we need to be more specific in our searches

Start by being very specific with your search phrases For example, if you were to put the word "insurance" in any search engine, you would get from 5,000 to 5 million responses Let it know what kind of insurance you are looking for and maybe even your location:

Example: auto insurance Phoenix Arizona

Unfortunantly, the above search condition will bring back any page that has any of the words in it, usually ranked by the pages that have all of the words to pages that have at least one.

To increase your chances of finding relevant information, learn how to use the "basic math" of search engines

USING THE SIGN TO ADD

In most cases, you want the search engine to only show you pages that have all of the words of a specific search The symbol tells the search engine to only bring back pages that have all of the words:

Example: auto insurance Phoenix Arizona

The above search condition would only show you sites that had all 4 words in it If you get too few results returned, it is too

specific The next step would be to eliminate one of the words:

Example: auto insurance Arizona

You can also use the symbol when you are overwhelmed with information Since "insurance" alone would give you way too many results, add motorcycle If it is still too many pages, add Arizona or whatever until you can narrow it down to dozens of pages instead of thousands.

USING THE - SIGN TO SUBTRACT

Sometimes, you want a search engine to find pages that have one word on them but not another word The - symbol lets you do this.

For example, if you wanted to search for infomation on sites that had computers, but did not want to see any Mac info, you would use the following:

computers -mac

That tells the search engine to find pages that mention "computers" and then to remove any of them that also mention "mac."

Or let's say that you wanted computer information, but did not want anything from certain venders:

computers -packard bell -mac -emachines

The - symbol is a great way to reduce results when you get too many that are unrelated to your topic Just start subtracting terms you know are not of interest, and you should get better results.

USING QUOTATION MARKS " " TO MULTIPLY

multiplying terms through a "phrase search" can be a much better way to get the answers you are looking for.

The above example of:

auto insurance Arizona

would bring back any site that had all three words anywhere on the page, which may or may not give you what you were looking for Using a phrase search would actually bring back different results because the exact phrase must be on the page.

"Arizona auto insurance"

would require that exact phrase to appear on the page in order to qualify This will quickly reduce the number of pages that are returned vs the addition method.

COMBINING SYMBOLS (ADVANCED MATH SEARCHES)

Once you've mastered adding, subtracting and multiplying, you can combine symbols to easily create targeted searches.

If you were looking for computers, but did not want Apple products, but you did want something that had 128 MB of RAM, you might use the following search condition:

computers -apple "128 MB RAM"

These basic math techniques work on virtually all major search engines and are generally easier to master than the the "boolean" search methods of "and, or, not, near, etc".

About the author

Posted by Ken Colburn of Data Doctors on July 17, 2000

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