PREDICATION OF CAREER BY ANALYZING USER’S BROWSER HISTORY, PERSONALITY TRAITS AND ACADEMIC RECORDS(DREAM MANTRA)

Afiya Sayyed, Gauri Darekar, Jayshri Jaiswal, Shruti Khandagale, Prof. A. V. Kanade

Abstract


Nowadays, choosing a right career is one of the most important aspects of the student’s learning process, and it is difficult to choose the right career option when there are number of options available to choose from. Our students choose academics based on traditional process and very little to no data mining or analytics is used to suggest right academics that can otherwise dramatically improve student’s performance. It is normal human tendency to choose a career only by considering the academic records without much analyzing the skills or interest of students.  Therefore, the proposed system aims at predicting the interest of user.  When it comes to prediction there has to be some information to perform mining on. And what could be better to collect information from the internet. Internet being widely popular among the student’s community can be a great source to collect information about an individual’s choice of interest. Therefore, the proposed system recommends using the browser history which will give an insight of what an individual is interested in. However, it is also observed that there is an impact of psychological parameters for choosing a right career option. Hence, the proposed system takes the psychological parameters into consideration as well. The psychometric test can be conducted on students and the students can be classified for choosing the right career option. Hence our Dream Mantra application is likely to recommend you that which career type will be best suited for you so you may take the right steps at the right time.


Keywords


Web Mining, Career, Psychological parameter, academic performance.

Full Text:

PDF

References


Xipei Luo, Jing Wang, Qiwei Shen, Jingyu Wang and Qi Qi, , “User Behavior Analysis Based on User Interest by Web Log Mining”,2017.

Akshi Kumar, Aditi Sharma, Sidhant Sharma, Sashyap Kashyap, “Performance analysis of Keyword extraction algorithms assessing extractive text summarization.”,2017

Cheng Lei, Kin Fun Li “Academic Performance Predictors” 2015

Luca Ponzanelli, Simone Scalabrino, Gabriele Bavota, Andrea Mocci, “Supporting Software Developers with a Holistic Recommender System”,2017

Pengwei Guo, Bin Zhang, Yin Zhang “Ranking Search Results Based on Combination of Interests.” 2016

Hidayet Takci; Kali Gurkahraman; Ahmet Firat Yelkuvan 2017 Federated Conference on Computer Science and Information Systems (FedCSIS) “Measurement of the appropriateness in career selection of the high school students by using data mining algorithms: A case study’’, page 113 – 117,Year: 2017 .

Tismy Devasia; Vinushree T P; Vinayak Hegde (2016).” Prediction of students performance using Educational Data Mining” 2016 International Conference on Data Mining and Advanced Computing (SAPIENCE), Ernakulam, India, IEEE.

Hidayet Takci; Kali Gurkahraman; Ahmet Firat Yelkuvan 2017 Federated Conference on Computer Science and Information Systems (FedCSIS) “Measurement of the appropriateness in career selection of the high school students by using data mining algorithms: A case study’’, page 113 – 117,Year: 2017.

Muhammad Fahim Uddin1, Jeongkyu Lee2. “Predicting Good Fit Students by Correlating Relevant

Personality Traits with Academic/Career Data” .2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

Ashish Nanda, Rohit Omanwar, Bharat Deshpande, “Implicitly Learning a User Interest Profile for Personalization of Web Search using Collaborative Filtering”,2014

Dropout Rate of Students,” Int. J. Multidiscip. Sci. Eng., vol. 3, pp. 35–39, 2012.

Y. Liu, L. Zhang, L. Nie, Y. Yan, and D. S. Rosenblum, “Fortune teller: Predicting your career path.” in AAAI, 2016, pp. 2017–2017.


Refbacks

  • There are currently no refbacks.




Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2019 INTERNATIONAL EDUCATION AND RESEARCH JOURNAL