“STUDY OF SEMANTIC WEB BAS`ED E-RECRUITMENT SYSTEM : REVIEW”

: Data retrieval of existing online recruitment systems on the basis of exact match finding techniques of user’s stored profiles and the recruiter’s requirement is an addressable issue nowadays. Despite of eligibility criteria all the exact details of an applicant does not match the recruiter’s online form leading to zero results. Several Ontologies have been popular in the field of knowledge management and knowledge sharing, especially after the evolution of the Semantic Web. Ontology defines the terms and concepts (meaning) used to describe and represent an area of knowledge. The aim of this research is to review the existing Ontologies developed for e – recruitment. In this paper I have done a review and analysis of semantic web based e – recruitment systems with their different concepts undertaken for their development. It involves study of different job portals for domain terminology, different semantic technology used so far for similar purpose, development of Ontology, Development and testing of SPARQL queries for accurate searching, Deployment over the Internet to conduct practical search . I have explained the e-recruitment process and methods listing them through several sections and drawn the conclusion.


INTRODUCTION E-recruitment
Recruiting suitable candidates online for the vacant jobs with the help of recruitment websites using different online resources is known as e-recruitment.It is the general practice of using different Web-based resources for searching, matching, checking, reviewing, interviewing and hiring new applicants (job seekers) in an efficient and effective way.

Benefits of E-Recruitment
 Free form filling and flexible recruitment process in comparison to physical recruitment process. Reducing cost of advertisement and marketing. Does not involve any intermediaries. Job seeker can apply in any part of the world and explore the entire world job vacancies at any time 24 x 7.  The Recruiting Company and the Job applicant, both shall have the benefit of meeting each other online through the job portal developed.The Recruiting Company post their job requirements online and the suitable candidate can fill in his profile for the vacancy. Costs less time in hiring the suitable candidate for the job. Hiring the Right match for the Right job through E-Recruitment, by matching the applicants resume with the job profile. The recruitment process becomes more efficient and easy to record details of the applicant. Nowadays Monster.com,Naukri.com,indeed.com,GoogleforJobs are few online recruitment websites providing multiple forms to suit the candidates eligibility criteria with the hiring firms requirement on WWW.
Limitations of E-Recruitment  Data retrieval in the current e-recruitment process is based on the exact match of the job and the applicant's details.  Still companies cannot rely fully on Internet for hiring suitable candidates. Meeting in person is also an important aspect to know and understand the job applicant. In many parts of India still Internet has not gained much popularity since internet penetration and awareness among people is much less.

ONTOLOGY
Ontology is defined as formal naming specification of shared conceptualization exploring the interrelationship between entities which actually exist in the source domain.
In brief, it is a study of different things that exist and the existing entities in the world.It is derived from the Greek word onto (being) and logia (written or spoken discourse).It is a branch of metaphysics , the study of first principles or the essence of things.
Ontology has different definitions in different fields.In Artificial Intelligence, it is the "the specification of conceptualizations, used to help programs and humans share knowledge."According to Tom Gruber, an AI specialist at Stanford University.In IT field, it is defined as formal naming specification of shared concepts like entities, attributes, events and their relationship to enable creation of a agreed vocabulary of terms for information exchange.
After the evolution of Semantic Web ontologies have been popular in the field of knowledge management and knowledge.Any area of knowledge can be easily defined by the Ontology which defines its terms and concepts (meaning).It has four basic components namely concepts, relationship, instances and axioms.

SEMANTIC WEB
The World Wide Web Consortium (W3C) promoted common formats for data on the World Wide Web.It aims at converting the current web of unstructured documents into a "web of data".It builds on the W3C's Resource Description Framework (RDF).The architecture of semantic web is illustrated in the figure below.The first layer, URI and Unicode, follows the important features of the existing WWW.Unicode is a standard of encoding international character sets and it allows all different languages to be used in one standard form.Uniform Resource Identifier (URI) is a string of a standard format that allows unique identification of resources.A subset of URI is Uniform Resource Locator (URL), which contains access mechanism and a (network) location of a document -such as http://www.example.org/.It offers solution, capturing and exploiting the meaning of terms to transform the Web, from a platform that focuses on presenting information, to a platform that focuses on understanding and reasoning with information."The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation" [12].
--Tim Berners-Lee ii) Web Ontology Language (OWL) A language derived from description logics which offer more detailed ontology constructs over RDFS is OWL.It is syntactically embedded into RDF, so like RDFS, it provides additional standardized vocabulary.RDFS and OWL have semantics defined which can be used for reasoning within ontologies and knowledge bases described using these languages.To provide rules beyond the constructs available from these languages, rule languages are being standardized for the semantic web as well.
iii) Simple Protocol and RDF Query Language (SPARQL) SPARQL, a Simple Protocol and RDF Query Language are used for querying RDF data, RDFS and OWL ontologies.It is an SQL-like language that can be used for querying ontologies, but uses RDF triples and resources for both matching part of the query and for returning results of the query.It is also a protocol for working with RDF data.A person searched for the word "child-friendly hotel at the beach in Northern Germany" in Google.He found a website with the review of a hotel in Dubai.It was located as it contained the words "beach", "Germany", and "children".Upon closer inspection he noticed, however, that Germany was the country of origin of the customer who wrote the review, and his profile said "children: none"-hence the match for "children".A search engine just checks for matches of words.It is called a "Syntactic Web "as it searches for the results on the basis of matching of characters without understanding its meanings.Semantic Web tries to go a step further.A semantic application for hotel search could deal with the customer's request "childfriendly hotel at the beach in Northern Germany" in the following manner: • Linguistic analysis of the search query, for example, "Hotel" is a noun, "child-friendly" is an adjective and "with swimming at the beach" and "Northern Germany" is adverbial particles.• Synonym used, for example, "family-friendly" is something similar to "child-friendly".
• Reasoning, as Northern Germany is a part of Germany, adjoins both North and Baltic Sea, seas have beaches etc.
• Matching is done here by finding hotels that match closely with the description.
In contrast to the Syntactic Web, any application of the Semantic Web would understand the search keywords similar to human beings and draws conclusions.

E-RECRUITMENT SCENARIO
For building ontology we first identified the sub-domains of the application setting like skills, professions types, etc. and several useful knowledge sources covering them.Certain applications may need more complex Ontologies depending on the requirements and the goals of the applications.A usual recruitment process seen from the organization's viewpoint can be divided into four phases: This paper presents a 3-tier system that models serialized documents of the applicants" worth and they are analyzed using document retrieval and natural language processing techniques for a human-like assessment.Its presentation tier was developed using java server pages and middle tier functionalities using web service technology.The data tier models résumés that have been tokenized and tagged using Brill Algorithm with my sequel.Within the middle tier, indexing was achieved using an inverted index whose terms are noun phrases extracted from résumés that have been tokenized and tagged using Brill Algorithm.-Rewriting rules more human-oriented.Combination of both is most promising [7] In addition to the research shown section [3] of Literature Review, the below figure no.5focuses on the study of the research on the development of vacancy recommendation that involves i) job vacancy modeling through data from occupational standards, ii) Searching job through skill, qualification and experience data from the job seeker's individual-assessment along with evaluation of their social connections; and iii) Matching the job seeker requirement to the job vacancy requirement.

CONCLUSION AND FUTURE WORK
In this paper, we reviewed different Ontologies that are used for development of e-Recruitment systems online and defined its architecture along with different technologies.
There are many research papers that discusses about the different ontological framework to provide online recruitment using semantic web, increasing and improving the skill analysis, skill measurement and recruitment process.Also research has been done showing collecting data from the social networking sites and filtering them and connecting them with the e-recruitment sites enabling easy data fetching and improving job recommendations.Also it focused on the different types of skill set of job seeker namely desired skills and required skills and enabled a better platform for allocating right job to the right person.This study explores many future works for promoting erecruitment using semantic web connecting social networking sites and employees data stored in Human Resource departments of companies.Mainly a prototype could be developed improving e-recruitment efficiency and effectiveness.Secondly, physical certificates can also help to validate the applicant's data analysis and lastly, various experiments should be conducted to prove the actual implementation and usability in today's semantic network.

Figure 1 :
Figure 1: OOP paradigm in ontology development for KBE system [9].Ontology building tools[13] 1) Protégé 3.4 is a knowledge based ontology editor providing graphical user interface.It provides better flexibility and enables the construction of domain ontologies.2) IsaViz is a visual environment for browsing and authoring RDF models as graphs.3) Apollo is a user-friendly knowledge modelling tool.The modelling is based around the basic primitives, such as classes, instances, functions, relations among application.4) SWOOP is a Web-based OWL ontology editor and browser.SWOOP contains OWL validation and offers various OWL presentation syntax views.

Figure 2 .
Figure 2.Semantic web layers (Fgure by Tim Berners-Lee, http://www.w3c.org/2000/Talks/1206-xml2k-tbl/slide10-0.html[10]XML Extensible Markup Language (XML) layer with XML namespace and XML schema definitions makes sure that it follows a common syntax for terms used in the semantic web.It is a general purpose markup language for documents containing structured information.It contains elements that can be nested and that may have attributes and content.It allows specifying different markup vocabularies in one XML document.i) Resource Description Framework (RDF).A Resource Description Framework (RDF) is a data representation format.It represents resource information in a graph form.It was basically intended for representing metadata about WWW resources, such as the title, author, and modification date of a Web page.It can also be used for storing any other data.It is based on triples subjectpredicate-object that form graph of data.All data in the semantic web use RDF as the primary representation language.ii)Web Ontology Language (OWL) A language derived from description logics which offer more detailed ontology constructs over RDFS is OWL.It is syntactically embedded into RDF, so like RDFS, it provides additional standardized vocabulary.RDFS and OWL have semantics defined which can be used for reasoning within ontologies and knowledge bases described using these languages.To provide rules beyond the constructs available from these languages, rule languages are being standardized for the semantic web as well.iii)Simple Protocol and RDF Query Language (SPARQL) SPARQL, a Simple Protocol and RDF Query Language are used for querying RDF data, RDFS and OWL ontologies.It is an SQL-like language that can be used for querying ontologies, but uses RDF triples and resources for both matching part of the query and for returning results of the query.It is also a protocol for working with RDF data.
IV.Comparison of WWW and Semantic Web Today's Scenario: The Syntactic Web: A syntactic web is a place where computers do the presentation easy and people do the linking and interpreting, which is actually a tough work.[Hendler & Miller 02].The Syntactic Web the following difficulties are observed namely.. • Locating information in data repositories • Travel enquiries • Prices of goods and services • Complex queries involving background knowledge • To book an Hotel not too far away from city and place is calm and cool and weather is pleasant Why we need to add Semantics?Ontologies are used to specify the meaning of annotations.Ontologies provide a vocabulary of terms.It derives new terms by combining existing ones.Meaning (Semantics) of such terms is formally specified and to specify relationships between terms in multiple ontologies.Let's understand the concept using a Travel example [11].

Figure 5 .
Figure 5. Components of Context-Aware Vacancy Recommendation [3]In addition to the research shown section[5] of Literature Review, the below figure no 6.shows development of semantic match making process should occur in three steps.The first step should include a standard common language model which defines standards for representing job recruitment information and job seeking contexts in the semantic format.The second step targets annotation, where information provided by users (in job advertisements and résumés) is "augmented" with meta-data retrieved from the

LITERATURE REVIEW Sr. No. Author Title Name of Journal / Research paper Year Technique and Conclusion Limitation and Future Work
1. Requirements analysis 2. Publishing the job posting 3. Receiving and pre-selecting applications 4. Final recruitment decision.The below figure describes the recruitment process for IT DomainFigure 4 .Ontology FlowChart for IT Carrier recruitment [12] 5. -To use ontology in developing a job recommender system, this helps to automatically match job offers with the candidates' profiles and viceversa.-proposed a Java based architecture to implement the e-Recruitment platform.-To convert the users' input into RDF description, RDF2Go and RDFBeans APIs are employed.