Improving Job Recommendation Using Ontological Modeling and User Profiles
| Autor: | C. Marimuthu, K. Chandrasekaran, Vedasamhitha Abburu, S.R. Rimitha, Annem Kiranmai |
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| Rok vydání: | 2019 |
| Předmět: |
User profile
Information retrieval Computer science 050901 criminology 05 social sciences A domain Conceptual model (computer science) Ontology (information science) Recommender system Knowledge-based systems 0501 psychology and cognitive sciences 0509 other social sciences Representation (mathematics) Relevant information 050104 developmental & child psychology |
| Zdroj: | 2019 Fifteenth International Conference on Information Processing (ICINPRO). |
| DOI: | 10.1109/icinpro47689.2019.9092271 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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