1. ENCHANCING EMPLOYEE COMPETENCE USING BEST FITTED TALENT RECOMMMENDATION ALGORITHM
Ramakrishnan R
ME CSE-PT
ANNA UNIVERSITY- MIT CAMPUS

2. ABSTRACT
Talent allocation, as a vital part of talent strategies, plays an important role in improving the utilization of talents.
However, it has encountered the problems, such as the lack of talent supply, low rate of talent utilization, etc.
In this mechanism, the concepts of talent-post match degree and talent utilization rate are introduced as evaluation criterion of talent optimal allocation.

3. LITERATURE SURVEY SL. NO TITLE OF THE PAPER JOURNAL SYSTEM DESIGN
HIGHLIGHTS
CHALLENGES
ALGORITHM / PERFORMANCE 1
Researches on the best-fitted talents recommendation algorithm
/15
2015 IEEE
th Chinese Control and Decision Conference
Based on the talent demand and the number of talents predicted by time sequence model, a dynamic planning algorithm is adopted after formula derivation to recommend best-fitted talents list.
Experimental results show that this best-fitted talent recommendation mechanism possesses higher utilization and is of use to the government department in talent management.
Possess highest talent utilization ratio and talent-post match degree
Talent-post match degree and talent utilization ratio are introduced as evaluation criterion
of talent optimal allocation
Time sequence model is applied to explore the distribution law of talents and predict number of talents
Dynamic programming algorithm

4. LITERATURE SURVEY SL. NO TITLE OF THE PAPER JOURNAL SYSTEM DESIGN
HIGHLIGHTS
CHALLENGES
ALGORITHM / PERFORMANCE 2
Information Retrieval, Fusion, Completion, and Clustering for
Employee Expertise Estimation
2016 IEEE International Conference on Big Data (Big Data)
Using a novel big data workflow with components of information retrieval and search, data fusion, matrix completion, and ordinal regression clustering,
find evidence of expertise and determine appropriate evidence weights for different queries and data sources that we merge
and present in a manner consumable by businesspeople.
Specialization, and collective intelligence are accelerated when organizations and even society-at-large has a proper inventory of
the expertise of all individuals because information and communication technologies can then be used to allocate
human capital
The current output depths of expertise (very deep, deep, moderate, some, limited) are only valid within the data set.
The labels have no external
calibration, which could certainly have different data sources than the internal data
Interior-point algorithms or accelerated proximal gradient Machine learning algorithms(supervised learning, support vector)

5. LITERATURE SURVEY SL. NO TITLE OF THE PAPER JOURNAL SYSTEM DESIGN
HIGHLIGHTS
CHALLENGES
ALGORITHM / PERFORMANCE 3
Big data analysis on the relationship between the organizational career management
and knowledge workers’ work involved
2016 IEEE TrustComBigDataSE-ISPA
The big data analysis
technological constructs the organizational career management of knowledge type staff involved in the theoretical model of mechanism.
Fair promotion, career information, pay attention to training, vocational self cognitive
and the employee's work involved in a positive correlation relationship, puts forward the corresponding organizational
career management countermeasures.
OCM(Organization Carrer Management) methodology.

6. LITERATURE SURVEY SL. NO TITLE OF THE PAPER JOURNAL HIGHLIGHTS
CHALLENGES
ALGORITHM / PERFORMANCE 4
Application of Neural Networks in Talent Management
2013 International Conference on Electrical Information and Communication Technology (EICT) /13
Talent classification process which is free from biasing and nepotism.
Talent Matrix

7. EXISTING SYSTEM

8. PROPOSED SYSTEM

9. HARDWARE REQUIREMENT Dual-core 64-bit processor 8 GB of memory
Up to 24 GB of internal storage (Kony Visualizer: 4GB, Android SDK: 2GB, Windows SDK: 4GB, BlackBerry NDK: 4GB, plus ample space for multiple complex projects)
Network interface card

10. SOFTWARE REQUIREMENT Name Software Operating System
Windows 10, Windows 8.1 Update, Windows 8, and Windows 7.
Front End
ASP MVC 5 .NET Framework, Microsoft Visual Studio 2013
Back End
Microsoft SQL Server 2012

11. CONCLUSION
The concepts of talent-post match degree and talent utilization rate are introduced as evaluation criterion of talent optimal allocation. Meanwhile, time sequence model is applied to explore the distribution law of talents and predict number of talents in the future.
Based on the talent demand and the number of talents predicted by time sequence model, a dynamic planning algorithm is adopted after formula derivation to recommend best-fitted talents list

12. REFERENCES
William A. Schiemann, et al, From talent management to talent optimization, Journal of World Business, No.49, 281–288, 2014.
Sanne Nijs, et al, A multidisciplinary review into the definition, operationalization, and measurement of talent, Journal of World Business, No.49, , 2014.
Gutteridge T G. “ Organizational career development systems˖The state of the practice” ,San Francisco: Jossey-Bass Publishers,
R. L. Martin, “The rise (and likely fall) of the talent economy,” Harvard Bus. Rev., Oct
K. R. Varshney, V. Chenthamarakshan, S. W. Fancher, J. Wang, D. Fang, and A. Mojsilovic, “Predicting employee ´ expertise for talent management in the enterprise,” in KDD, 2014, pp –1738.
Herriot, P, Gibbons, P, Pemberton, C, Jackson, P. R.. “An Em-pirical Model of Managerial Careers in Organizations”. BritishJournal of Management, 1994, (5):
Crabtree MJ. “Employees Perception of Career Management Practices: The Development of a New Measure”Journal of Career Assessment,1999. [4] SalehSD, Hosek J. “Job involvement: concepts and measurements”.Academy of Management Journal,1976,19: