Tuesday 29 June 2010

The 4 Seperate Components To Semantics Within ZubedJobs.com

Semantic Technologies in Zubed

The technologies that we are developing relevant to matching candidates to jobs can be split in four key areas

1 Pre processing unstructured text leading to structured information
2 Using metadata to aid matching
3 Vectorial Semantic Analysis
4 Vectorial Semantics on Structured Data

Today lets look at number 1.

By using semantically enabled systems, we are able to take unstructured text (such as a Job Ad or CV) and extract valuable information. This is often called metadata. Semantics, along with other core Artificial Intelligence technologies, allows us to do this by enhancing the systems ability to understand the text. The technique effectively creates structured and enhanced information in a common form that can be used to significantly enhance a systems abilities to match Jobs to candidates.

We are using semantically enabled parsers in four areas to allow us match jobs to candidates and plot them all on a map.

• finding a company website and location details so that we identify job vacancies with a company and location
• Intelligently browsing a website to locate job pages by identify the routes to possible job pages semantically
• Parsing possible job pages, deciding whether the page is a job or not, finding the location, extracting all the relevant information about the job (skills required (soft and hard), Job title, Job Sector (engineering medical etc) , storing all this relevant information and then plotting the job on a map

These first three uses together we have called Semantically Enabled Intelligent Job Mining and effectively constitutes our search engine for jobs

The fourth process is a CV parser. After extracting the details of the candidate, deconstruct the CV into its constituent parts (e.g. Employment Records, Education , Skills, References etc) and building up a profile of the candidate. Using our advanced technologies we can extract much detail. Take the employment record below, for instance:

_________________________________________________

Project Manager (Aug 2006–Jun 2008)
My First Company Ltd London, UK
Was the project manager, for the charity’s Drugs Awareness project, the project’s aim was to educate the local community on the effects and wide reaching effects of Drug Abuse/misuse.
Recruited a motivated, dedicated project team.
Prepared the Project Soft-Launch and developed the project to fruition.
_____________________________________________

Our system conveniently stores the facts that our candidate was a project manager for nearly 2 years. The candidate worked in the medical sector and has specialism’s in Drugs Awareness and Abuse. Finally identifying that during this 2 year period, our candidate was also involved in recruitment and project development.

Stay tuned for numbers 2, 3 and 4.

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