What is meaning of "normalization" in reference to geocoding? - geolocation

What is meaning of "normalization" in reference to geocoding? I understand that geocoding is the trasnformation of string address to latitude and longitude. However, I don't understand what "normalization" serves for?

I work with geocoding at SmartyStreets and have not run into the term "normalization" in reference to geocoding. My first inclination is that it could more likely refer to "standardization". In other words, normalization in the context of geocoding could mean cleaning the data and putting it into a standard or expected format. This standard or expected format would depend entirely on whatever application or service that is handling the data.

Related

Google geocoding API Inner Workings

I'm currently working with some large datasets that include some location based information but lack direct latitude and longitude measurements which I need in order to create visualizations.
In order to resolve this problem, I've been using geocoding APIs that require addresses or address-like information as input and provide latitude and longitude information as output.
I started by using the Nominatim API. Unfortunately, due to the nature of the address-like data that I have, many of my queries failed so I started using the Google geocoding API. The Google API provided me with a significantly higher success rate, but it is a paid API which is not ideal.
I realize that given the incredible resources that Google has that it would be virtually impossible to build a system that rivals their geocoding API within a reasonable amount of time, but it's made me wonder what's going on under the hood.
Is a BERT-like translational system at work? What happens to the text after it's sent off?
I'm using n-grams for similar usage by creating an index and an inverted index. See this package ngram
import ngram
...
country = filename.replace('.csv', '')
ind[country] = ngram.NGram()
inv[country] = {}
s_csv = csv.reader(stream, delimiter=';')
next(s_csv)
for row in s_csv:
coord = tuple(map(float, row[0:2]))
ad = ' '.join(row[2:]).lower()
ind[country].add(ad)
inv[country][ad] = (coord, address)
then you can use the find function
Take care of the memory consumption ~16GB RAM for a country like France and OSM Data
To see an implementation of that, check this OpenGeoCode HTTP API Service source code

Understanding data cache locality in mips code

I have been browsing stackoverflow could not really find a example regarding to this one. I understand the concept of Temporal and Spatial locality for data cache:
Temporarl locality: address revisited
Spatial locality: every x times memory access get a hit
But how does it look like in the mips code? Can anyone give concrete examples and show how it works?
Spatial and temporal localities are not related to a specific architecture, mips or another one. It is more a property of programs and on the way they are processed on a computer.
Temporal locality states that if you access a given memory location, it is very likely that the same location will be accessed a few time after.
Difficult to give a specific example, but the idea is that if, for instance, you modify a variable, there is a high probability that this variable will be used a few instructions after in the program. Of course, it is possible to find counter-examples, but most of the time when a computation is done and stored in a variable, it is because we will need later the result of this operation.
The definition that you give of spatial locality is incorrect. Spatial locality states that if an information in some memory location is required, it is very likely that other informations located in a nearby memory location will also be required some time after.
This property is due the fact that many constructs of programming languages correspond to data stored in consecutive memory locations. This includes :
elements of an array
fields of a struct
local variables that are in successive addresses in the stack
parameter of a function that are also close in the stack
Again, it is possible to find counter-examples, but if, for instance, one accesses the firt character of a string, it is probably to do some kind of computation, search or whatever on the string, and most of the time, the other chars of the string will also be accessed.

How to use latitude and longitude in a Zillow search url

When searching on Zillow using an address, the URL looks like this:
http://www.zillow.com/homes/{Street}", -"{City}," -"{State}" "{PostalCode}_rb/
However, there seems to be no documentation regarding the use of geographic coordinates in such a url.
How to use latitude and longitude instead of an address?
An answer in Can I search Zillow using latitude and longitude coordinates? - Zillow Questions (the 1st Google result on "Zillow search by coordinates") dated 03.2015 gives an example:
http://www.zillow.com/homes/#/homes/for_sale/fsba,fsbo,new_lt/1_pnd/88.769211,-70.092773,-90,-158.686523_rect/3_zm/0_mmm/
Testing shows that only the http://www.zillow.com/homes and /88.769211,-70.092773,-90,-158.686523_rect parts are required.
It's x0,y0,x1,y1 (the direction between the points can be any). (The coordinates in the example are quite strange and specify an area up to the North Pole. More realistic ones are e.g. 53.67068,-71.323242,13.453737,-127.045898_rect.)
Since the last test, the technique stopped working. Moreover, coordinates appear to have vanished from property details as well!
There is no way provided to bring up a specific object by coordinates - they are instead uniquely identified by an ID (ZPID - Zillow Property ID) - and the way to bring up one as of now is e.g. http://www.zillow.com/homedetails/7044216_zpid/.
A possible reason is there's no way to guarantee that coordinates identify anything or identify something uniquely. I.e. coordinates are conceptually a search term rather than a means of identification.
Finally, do keep in mind that all this is undocumented and is subject to change (you can already see one quite-a-change above). They only support API as the means to access their services programmatically.

Get location data when out of service

I'm working on a iPhone app that stores location data from a user. However, sometime the user doesn't have service.
Is there an API that estimates location data when the phone gets back into service? Or any other suggestions
No, there is no such API, because that would create wrong locations.
You have to write yourself such a method, that hopefully works in the scope of your application demands:
E.g You could do a linear interpolation when the GPS service has an outage for some seconds.
e.g:
A liner interpolation of lat and lon values work without special geographic calculations.
Just it would not work if you cross the datum limit (border longitude = 180E to 180 W),
and maybe not if you cross the poles.
But both situations will practically not happen.

Altitude Disappears from MKPlacemark

So I have some code that gets the user's location from the phone as a CLLocation, then I do a reverse geocode on it. The problem is that the resulting MKPlacemark has 0 for altitude, despite the fact that the CLLocation had a value in the altitude field.
It makes sense that if I just ask for the address of some coordinates, I don't necessarily get altitude (as that would require topographic logic). Most of the questions on here suggest calling out to a topo service.
I am wondering why the reverse geocoder would not just preserve the altitude, and also asking people what their preferred solution has been to this problem. It's not like it's hard to figure out: I can pass the altitude in separately and then just jam it into my ultimate object (my own address class), but that's ugly.
This is indeed the state of these classes at this time. Probably a bug report with Apple is in order.

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