Implementation-Ontological Learning for Analysis of User Preferences
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

Research Paper | Computer Science & Engineering | India | Volume 6 Issue 4, April 2017

Implementation-Ontological Learning for Analysis of User Preferences

Dhanshri Karbhari, Priya Sharma, Sharvari Patil, Sukanya Naikar

Ontological researches have been carried out in highly diverse deployment in the past few decades for number of purposes from social networks to e commerce for mapping user preferences and profiles. Apart from this, the ontological approach can be used to map preferences of users on a job portal. Ontological application for online recruitment is now becoming a crucial task for matching job listings and applicants semantically in a highly unstructured semantic web environment using ontology and ontological matching techniques. Most of the current research is focused towards available widespread standards and classifications to build human resources ontology that provides a semantic representation for the positions offered and the best candidates to fill in those places. Some of the other research had been done where they created their own HR Ontology to build recruitment prototype. In the proposed system, we provide a work based mapping for the Ontology. In the work based ontological mapping, the system provides us with exact capabilities which are required for an individual to fetch the job. The job requirements are then matched against the most ontologically suitable profile to get the best match

Keywords: User preferences, Generalization, Sampling, Ontological mapping, Implementation

Edition: Volume 6 Issue 4, April 2017

Pages: 825 - 827

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How to Cite this Article?

Dhanshri Karbhari, Priya Sharma, Sharvari Patil, Sukanya Naikar, "Implementation-Ontological Learning for Analysis of User Preferences", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20172503, Volume 6 Issue 4, April 2017, 825 - 827

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