Advertisement

ADHYAYAN—An Innovative Interest Finder and Career Guidance Application

  • Akshay TalkeEmail author
  • Virendra Patil
  • Sanyam Raj
  • Rohit Kr. Singh
  • Ameya Jawalgekar
  • Anand Bhosale
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 906)

Abstract

ADHYAYAN is an innovative mobile application which determines a user’s interest in a particular domain and nurtures them effectively so that they can pursue career in the field which they are interested in. The system takes into account social media posts, results of a test and application activity to find out the interest of users in different fields and then assists, guides and evaluates them continuously to improve their skills in these fields. ADHYAYAN is a three-tier system which consists of a front-end, middle layer, and back-end. Front-end is an Android application which provides personalized GUI for each user. Middle layer is Firebase, while back-end is a server hosted on ‘Google Cloud Platform’. An algorithm has been developed for ADHYAYAN which calculates the ratio of user’s interest in different domains and eventually feeds are generated in the same ratio on user’s profile. To cater the increasing need of skilled employees in different fields and promote interest-based learning, ADHYAYAN has been proposed to overcome various limitations and drawbacks of existing solutions.

Keywords

Unemployability Social media Continuous evaluation Test Feeds Profile Skills Career Short term profile Long term profile Personalized Real-time 

References

  1. 1.
    Problems in Indian Education System. http://surejob.in/10-fundamental-problems-with-education-system-in-india.html. Last accessed on April 29, 2018.
  2. 2.
    Gardener’s Theory of Multiple Intelligences. https://tinyurl.com/y98n7gyf. Last accessed on April 27, 2018.
  3. 3.
    Tiffany Iskander, E., Gore, P., Bergerson, A. A., & Furse, C. (2013). Gender disparity in engineering: Results and analysis from school counsellors survey and national vignette. In 2013 IEEE Antennas and Propagation Society International Symposium (APSURSI).Google Scholar
  4. 4.
    Alimam, M. A., Seghiouer, H., El Yusufi, Y. (2014). Building profiles based on ontology for career recommendation in E-Ieaming context. In International Conference on Multimedia Computing and Systems (ICMCS).Google Scholar
  5. 5.
    Pisalayon, N., Sae-Lim, J., Rojanasit, N., & Chiravirakul, P. (2017). Identifying personal skills and possible fields of study based on personal interests on social media content. In 6th ICT International Student Project Conference (ICT-ISPC).Google Scholar
  6. 6.
    Twitter API. https://developer.twitter.com/en/docs. Last accessed on April 29, 2018.
  7. 7.
    Google Cloud Vision API. https://cloud.google.com/vision/docs/. Last accessed on April 29, 2018.
  8. 8.
    DatumBox API. http://www.datumbox.com/machine-learning-api/. Last accessed on April 29, 2018.
  9. 9.
    Meetup API. https://tinyurl.com/yaaqf7r4. Last accessed on April 27, 2018.
  10. 10.
    News API. https://newsapi.org/. Last accessed on April 29, 2018.
  11. 11.
    Avicii. https://en.wikipedia.org/wiki/Avicii. Last accessed on April 29, 2018.
  12. 12.
    Unemployability is a bigger crisis than unemployment, says Kalam. https://tinyurl.com/y9q65yc8. Last accessed on April 29, 2018.

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Akshay Talke
    • 1
    Email author
  • Virendra Patil
    • 1
  • Sanyam Raj
    • 1
  • Rohit Kr. Singh
    • 1
  • Ameya Jawalgekar
    • 1
  • Anand Bhosale
    • 1
  1. 1.International Institute of Information Technology (IIIT)PuneIndia

Personalised recommendations