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Finding Career Paths

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ruby childs

on 31 March 2014

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Transcript of Finding Career Paths

The Problem
Understanding in Mass
Company path
Organisation of Data
Finding Career Paths
By Ruby Childs
Cleaning Data
What job do you do now?

What job/education have you done?

What job do you want to have?
To predict possible career moves
of a jobseeker, from title, education and company
Jobseeker Experience
- Relational DB, MySQL

Company Names

Extensive project of cleaning company names
Removal of country, locations whilst keeping in mind 'Bank of China' for example
Manual processing
Graph Database
Nodes and edges to represent relationships
Most common in Social Networks
Implemented in Java
Add nodes: company entities
Add relationships (edges):
worked_at, progressed_to
Add number of jobseekers for edge weighting
Path with lowest cost from Node A to B
but we want highest cost for jobseekers.....
Solution: Invert weights: 1/no_jobseekers
Career Paths
Reverse inversion for each path
Worked at
Progressed to
weight: no of jobseekers
weight: no of jobseekers
Full transcript