Semantics Based Intelligent Job Portal

Abstract

Semantics based Intelligent Job Portal is a web application that will carry automated meaningful search on behalf of the user (Job Provider and Job Seeker) so that only precise and correct information is retrieved and both the users can find their right match, that is, Job Seekers find the right job and Employers find the right person for the job. The job portal takes data of job seekers from LinkedIn and as their CVs. Data is extracted from LinkedIn using its profile API. CVs can be provided either by filling data into online forms provided by portal or by uploading in PDF format. PDF Parser is a PHP library that is used to extract data from CVs in pdf format. Skills are separately extracted from this data. These extracted skills are individually mapped over relational database. Every new added skill is sent to google to get its Uniform Resource Identifier using Ajax call to google API. Different representations of skill names are stored with common URI in relational database. On the other hand, Job portal takes data of Job providers and their related companies. Job providers upload jobs on behalf of their companies. Skills are extracted from job and are mapped to relational database. Each skill is sent to google using AJAX call to get its URI. URI of skills are used to perform skill based search. Each URI from google is searched over the database and skills with same URIs are grouped together to achieve semantics using google as base ontology. Users can perform skill hunt loosely means without restricting themselves to actual spells of words. Companies are efficiently maintained over the portal. Interface of website is adaptive to increase usability of portal.