July 7, 2016 at 6:05 pm
The SoundEx fuzzy matching algorithm for comparing names dates back to Franklin Roosevelt era paper and microfilm records archiving.
https://www.census.gov/history/www/genealogy/decennial_census_records/soundex_1.html
"Do not seek to follow in the footsteps of the wise. Instead, seek what they sought." - Matsuo Basho
July 8, 2016 at 6:14 am
djackson 22568 (7/7/2016)
I am not sure of the background education of everyone here, but my guess is that there are at least a few people who are unaware of the issue with doing math with a processor.While processors absolutely are accurate when it comes to binary, they are not accurate when it comes to floating point calculations. One of my professors really enjoyed showing us how there is a margin of error. If you understand the conversion between binary and base 10, it becomes obvious why this is true. It has been too long for me to give an educated explanation of the reasoning behind it, but I am sure a Google search would provide insights.
The important thing to note is that it is absolutely possible for a computer to perform calculations and come up with a wrong answer.
I did a BSc in Physics (which included programming in Fortran) followed some years later, as a mature student, by an MSc in IT. One of the lecturers also had an obsession with number bases so besides base 10, binary, octal and hex he set us tasks with different bases such as 7 and 11. I will always remember that computers do not calculate exactly. This came up in one of my first jobs subsequently when the total of a bill was not quite the sum of the individual items!
July 8, 2016 at 6:39 am
TheFault (7/7/2016)
You could have just used pigeons! https://en.wikipedia.org/wiki/Project_Pigeon
Or this 😛
https://archive.google.com/pigeonrank/
...
-- FORTRAN manual for Xerox Computers --
July 8, 2016 at 7:52 am
TheFault (7/7/2016)
Iwas Bornready (7/7/2016)
Over forty years ago one of my advanced math classes had a problem about how to aim a moving sub's torpedo at a moving ship and hit it. Of course if you aim directly at the ship then by the time the torpedo gets there the ship has moved on. They solved this in various ways one way mathematically is using a formula that you keep re-iterating through using each result set as input into the next operation of the calculation until the margin of error becomes small enough that it is acceptable. There wasn't the exactness of adding up a column of numbers but the idea of approximate mathematically results is certainly not something new as in the image comparison example. You just keep comparing until your margin of error becomes small enough that it reaches a preset value.You could have just used pigeons! https://en.wikipedia.org/wiki/Project_Pigeon
Back in WW2 era, the military was investigating many ways to incorporate "furry logic" into their weapons systems.
https://en.wikipedia.org/wiki/Bat_bomb
https://en.wikipedia.org/wiki/Anti-tank_dog
"Do not seek to follow in the footsteps of the wise. Instead, seek what they sought." - Matsuo Basho
July 15, 2016 at 5:20 pm
djackson 22568 (7/7/2016)
I am not sure of the background education of everyone here, but my guess is that there are at least a few people who are unaware of the issue with doing math with a processor.While processors absolutely are accurate when it comes to binary, they are not accurate when it comes to floating point calculations. One of my professors really enjoyed showing us how there is a margin of error. If you understand the conversion between binary and base 10, it becomes obvious why this is true. It has been too long for me to give an educated explanation of the reasoning behind it, but I am sure a Google search would provide insights.
The current (since August 1987) floating point standard (IEEE 754) provides for numbers where the exponent indicates a power of 10 s well as where it indicates a power of 2, which eliminates the errors caused by conversion (because it eliminates the representation deficiencies which cause those errors). If you have hardware that supports that (and software that can use that hardware) the errors resulting from conversion disappear. There will of course still be rounding when it's needed, much as there is in arithmetic using the decimal/numeric fixed point type supported by SQL. It is impossible to represent numbers like 1/3 in decimal or binary, whether floating point or fixed point, indeed a proper rational notation is needed (either a numerator denominator pair, or a floating point format with an extra field indicating the base used) and algebraic numbers and transcendental numbers create some additional interesting problems.
The important thing to note is that it is absolutely possible for a computer to perform calculations and come up with a wrong answer.
Another important thing to remember is that it is equally possible for people to give the computer the wrong instructions for the task at hand. That is probably a bigger problem than the computer's limitations.
Tom
November 9, 2016 at 3:22 am
Sounds a bit like a hard wired shortcut in place of training neural networks.
Gaz
-- Stop your grinnin' and drop your linen...they're everywhere!!!
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