Finding the perfect place
Imagine that you have just gotten a job offer across the country and need to
relocate. Or, you have just retired and are looking for a good place to sit in
the sun. Or perhaps you just really hate the Midwest! What do you do? Sure
there is plenty of help out there once you’ve decided where you want to move
to. But how do you decide?
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There are tens of thousands of communities around the United States. Each one
has its good and bad points. The retiree in our example above might want a warm
climate, good access to medical care, and low property taxes. A couple with
young children might want to have good schools in their town. A hundred years
ago, few people ever moved more than a few miles, and they could gather their
information from friends and neighbors. Nowadays, when you might be moving from
New England to the West Coast, how do you decide exactly where to go?
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The amount of public information available about any given city, or town, or
even village, is vast. Whatever you think is important is almost
certainly out there somewhere. But where? And how? A truly
personalized search needs to take into account which of the hundreds of factors
out there are important to you. It also needs to take into account the
relative importance of the various factors. And not least, the search has to
take into account which ranges of the factors are important to you.
Let's illustrate with an example. Joe is retiring, and wants to move to a place
where he can enjoy nice weather, have a hospital nearby, where there are a lot
of other people his age, and where the property taxes are low, since he is on a
fixed income. Therefore, he wants to search for a place where the annual
precipitation is relatively low, where the average low temperature in January
is as high as possible, where the number of hospitals is as high as possible,
where property taxes are as low as possible, and where the median age of the
population is as close to 65 as possible. Joe assigns each of these factors a
weight of 20%.
As another example, Karen and Mike are parents of two children about to enter
kindergarten. They work near Boston, and want to find a place nearby where the
houses are relatively affordable, where the schools are excellent, and where
crime is reasonably low, although they are not too worried about that. They
assign house prices a weight of 30%, school achievement scores a weight of 30%,
school spending in a community a weight of 20%, distance from Boston a weight
of 10%, and crime rates a weight of 10%. For crime, they specify that anything
better than average for New England is fine.
Any search engine which is used for finding the right place to live has to be
flexible enough to handle these kinds of examples, as well as their obvious
extensions. It should be able to
find a city just like yours, but on the other side of the
country. It should be able to
quickly find cities for you, and rank them according to your own
criteria. If you don't have one ideal city, perhaps you can
build one , based on several others you know? You also
should be able to do
advanced optimization, which lets you select exactly what to look for.
All of the data must be there, but more importantly, the engine needs to know
what to do with the data. The real world is not black-and-white, but has a lot
of shades of color, and you want your search to distinguish more than just
"yes" or "no".
Try out our searches and see if they meet your needs. Have fun, and tell us what
you think.
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