Comprehensive Literature Review: Job Recommendation Systems

This literature review provides an overview of job recommendation systems, emphasizing the pivotal role of the internet in connecting job seekers with relevant opportunities. It explores key areas such as job matching algorithms, where online platforms use filters based on user-provided data to streamline job searches, and data visualization, which enables organizations to analyze human resource capital trends. The review also highlights the evolution of job searching from traditional methods to online platforms, which offer a wider array of opportunities and easier browsing. Furthermore, it underscores the growing importance of soft skills, such as communication, in addition to technical skills for employee success. The convergence of these elements shapes the landscape of modern job recommendation systems, enabling both employers and job seekers to make informed decisions in the ever-changing employment market. Desklib offers more solved assignments and past papers for students.

Running Head: LITERATURE REVIEW ON JOB RECOMMENDATION SYSTEM
LITERATURE REVIEW ON JOB RECOMMENDATION SYSTEM
NAME OF THE STUDENT
NAME OF THE UNIVERSITY
AUTHOR’S NOTE

1LITERATURE REVIEW ON JOB RECOMMENDATION SYSTEM
ABSTRACT
The Job Recommendation System has changed a lot over the years. With the advent of the
internet, the traditional means of finding a job such as the newspapers have lost their relevance.
Job seekers search for their preferred jobs in the internet based on their skill sets and their work
experience. The hiring agencies gather the information from the job search engines and then
recruit the preferred candidate. There has been a lot of research done on the topics of
employment and job searching; therefore, the relevant aspects are discussed elaborately, which
determines the aspects of Job Recommendation system.

2LITERATURE REVIEW ON JOB RECOMMENDATION SYSTEM
Table of Contents
INTRODUCTION...........................................................................................................................3
DISCUSSION..................................................................................................................................3
JOB MATCHING........................................................................................................................3
DATA VISUALIZATION..........................................................................................................3
JOB SEARCHING......................................................................................................................4
SOFT SKILLS RECOMMENDATION......................................................................................4
CONCLUSION................................................................................................................................5
REFERENCES................................................................................................................................6

3LITERATURE REVIEW ON JOB RECOMMENDATION SYSTEM
INTRODUCTION
Employment is one of the ever-dominant topics, which determine the future, as well as
the present of the world economy. The dynamics of employment opportunities for both the job
seeker as well as the employer keeps changing with the innovation and development of
technology. There has been numerous researches done on the aspects of job search but the most
relevant points have been enumerated in this literature review.
DISCUSSION
JOB MATCHING
The research done on job matching done by Cheng Kam Ching reveals that the internet,
which is the preferred application for job seekers to search for jobs, uses the filter mechanisms to
streamline the related jobs for the job seeker based on his/ her previous search criteria. The
online employment sites such as monster uses the information provided by the job seeker and
shortlists the related jobs based on the expertise and experience of the job seeker (Cheng, 2013).
The dynamics of job searching has changed completely since the arrival of the internet mainly
because it opens up a wide array of opportunities for the job seeker to choose from as well as
enables the user to easily browse through the job criteria in a hassle-free approach (Failla,
Melillo & Reichstein, 2017).

4LITERATURE REVIEW ON JOB RECOMMENDATION SYSTEM
DATA VISUALIZATION
Data visualization is the application to enable the people comprehends the available raw
data by interpreting it in a user-friendly application. The research done on the aspect of Job
Search by Faisal Abdulkreem Qasem Saeed reveals that the changing pattern in the human
resource capital was utilized by the organization. The organization, Halal training, used the
information provided in the form of graphs and charts and analyses them to check the correlation
between the organization’s hiring process and the changing dynamics in the human capital
resource (Fezarudin, Tan & Saeed, 2017). Finding the correlation between the two will provide
both the employer and the job seeker to understand the aspects of the current employment
scenario and enable both of them to take a good decision.
JOB SEARCHING
The dynamics of job searching has changed altogether since the arrival of the internet.
The advent of the internet has drastically reduced the relevance of newspapers and other
previously used sources of employment. The research done by Constantin Mang reveals that the
internet provides the job seeker to choose from a wide array of employment opportunities and
the method for the enabling job seekers to find the job according to their preference is done by
incorporating the data gathered from the job seekers using the German Socio- Economic Panel
(SOEP) and then matching those with the advertisements posted by the employers (Mang, 2012).
This makes it easier to streamline the job seekers into their preferred job destinations and the job
searching process becomes easier compared to the previous tedious process of finding jobs
manually on the newspapers or from other traditional sources.

5LITERATURE REVIEW ON JOB RECOMMENDATION SYSTEM
SOFT SKILLS RECOMMENDATION
Hard skills such as the technical knowledge, which are required for a job, are important
for the job but more than those, the soft skills such as the ability of the employee to communicate
effectively plays an important role in the success of the employee. Soft skills are the
interpersonal skills, which the employee possesses (Salleh et al., 2017). Soft skills are an
important aspect in today’s job market and the research done by Azuraini Abu Bakar reveals the
fact that soft skills are more important than the hard skills or the technical skills. The
organizations are hiring employees who possess both the soft skills as well as the hard skills
(Bakar & Ting, 2011). Merely possessing the hard skills or the technical skills cannot ensure the
success of the employees in the long run.
CONCLUSION
From the above review of the literature available on Job Recommendation System, it is
clear that the internet plays a dominant role in enabling the job seeker to find the relevant jobs.
The employer can get the most efficient and talented workers from the internet. It has also been
noticed that the soft skills plays a more important role in determining the success of an employee
than the hard skills or the technical skills.

6LITERATURE REVIEW ON JOB RECOMMENDATION SYSTEM
REFERENCES
Bakar, A. A., & Ting, C. Y. (2011, June). Soft skills recommendation systems for IT jobs: A
Bayesian network approach. In Data Mining and Optimization (DMO), 2011 3rd
Conference on (pp. 82-87). IEEE.
Cheng, K. C. (2013). Development of job matching algorithm with collective learning (Doctoral
dissertation, UTAR).
Failla, V., Melillo, F., & Reichstein, T. (2017). Entrepreneurship and employment stability—Job
matching, labor market value, and personal commitment. Journal of business venturing,
32(2), 162-177.
Fezarudin, F. Z., Tan, M. I. I., & Saeed, F. A. Q. (2017, August). Data Visualization for Human
Capital and Halal Training in Halal Industry Using Tableau Desktop. In Asian Simulation
Conference (pp. 593-604). Springer, Singapore.
Mang, C. (2012). Online job search and matching quality (No. 147). Ifo Working Paper.
Salleh, K. M., Sulaiman, N. L., Mohamad, M. M., & Sern, L. C. (2017). Assessing soft skills
components in science and technology programs within Malaysian Technical
Universities. Songklanakarin Journal of Science & Technology, 93(3).