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Title: Improving Job Recommendation Using Ontological Modeling and User Profiles
Authors: Rimitha S.R.
Abburu V.
Kiranmai A.
Marimuthu C.
Chandrasekaran K.
Issue Date: 2019
Citation: 2019 15th International Conference on Information Processing: Internet of Things, ICINPRO 2019 - Proceedings , Vol. , , p. -
Abstract: The recommendation system uses prior obtained information about the user to present user inteseted data. Personalized results aim to provide relevant information to the user based on the user's basic information or activity with the system. The user's basic information can be modeled into a user profile using ontology. Ontology is the systematic representation of various entities in a domain and the relationships between them. In this paper, we aim to present the conceptual model for a job recommendation system that uses ontology-based user profiles. The system collects basic information and models into a user profile. The dynamic aspects such as favorite jobs list and recently viewed jobs are then used as a source of data for the system. The recommendation algorithm works on the input given to present the list of relevant jobs to the user. © 2019 IEEE.
Appears in Collections:2. Conference Papers

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