In Progress

Address cleaning and landmarking (Partial Project)


Half of the project is done by our team. The developer whomever is interested in doing this project

must understand the project and develop second phase of it

following is the Discription.

Syntax corrections of the address string - remove incorrectly used punctuation marks such as using comma twice or hash signs.

Spell check of each attributes using either Google Maps API

Confirm City and Pin code for a given address again using Google Maps API

Using the Hash Function and Rabin Karp algorithm to classify new data. Additionally, check if same data has been cleansed previously, and find similar data.

Once data has been classified of an address, give it a reference, such as Address X containing A1 attribute, A2, A3….An where A1 is the left most attribute in an address string and A’n' being the right most attribute. Leave out the A1 attribute from the string, and refer the remaining string to google for GPS coordinates. If Google returns positively, then add the A1 attribute and refer this to Google for GPS coordinate. Again if the result is positive, then we have the GPS coordinate of the exact deliver address. If the result was negative when A1 attribute was left out of the search query, then leave out the A2 attribute as well and use the remaining string to convert it into a GPS coordinate using Google Maps API. Store this GPS coordinate against the original address string.

Post this, once the driver makes a deliver at the addresses, we get the actual GPS coordinate for the given address in case google wasn’t able to do so. At this point, we'll store the update GPS coordinate against this string. Please note that, each time a string is referred to Google MAPs API, store that string separately and the GPS coordinates received for it for use in the future.

Using Hash Table, create cross referenced landmarks for each address. E.g: Any address can act as a landmark to another address as long as they’re in the proximity. So using Hash Table and Hash Chain (equivalent to Block Chain) to create a link between two nodes/addresses in turn creating a structure known as Merkle tree. Merkle Tree structure will allow us to create Master Landmark, Slave Landmark Level 1, Slave Landmark Level 2, Slave Landmark Level 'n' hierarchy structure. So if we need to guide a biker to an address, we can guide him using multiple landmark for in order to get to a complex location and most locations are complex in India be it a residential society or a large block of office buildings. We can create marco to micro level landmarks for any given address.

Mandatory requirements:

Explain the entire project and it's know-how and the technology involved and how the technology/code accomplishes the goal

Help us implement and integrate the software in our current software

Support us if required post integration

Help us with testing post integration.


Skills: Java

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About the Employer:
( 1 review ) Chennai, India

Project ID: #15925768

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