Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Currency recognition system using image processing(Institute of Electrical and Electronics Engineers Inc., 2017) Abburu, V.; Gupta, S.; Rimitha, S.R.; Mulimani, M.; Koolagudi, S.G.In this paper, we propose a system for automated currency recognition using image processing techniques. The proposed method can be used for recognizing both the country or origin as well as the denomination or value of a given banknote. Only paper currencies have been considered. This method works by first identifying the country of origin using certain predefined areas of interest, and then extracting the denomination value using characteristics such as size, color, or text on the note, depending on how much the notes within the same country differ. We have considered 20 of the most traded currencies, as well as their denominations. Our system is able to accurately and quickly identify test notes. © 2017 IEEE.Item Improving Job Recommendation Using Ontological Modeling and User Profiles(Institute of Electrical and Electronics Engineers Inc., 2019) Rimitha, S.R.; Abburu, V.; Kiranmai, A.; Marimuthu, C.; Chandrasekaran, K.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.Item Ontologies to Model User Profiles in Personalized Job Recommendation(Institute of Electrical and Electronics Engineers Inc., 2019) Rimitha, S.R.; Abburu, V.; Kiranmai, A.; Chandrasekaran, K.Personalized recommendation aims to provide results that are likely to be of interest to a particular user. Personalized recommendation is useful in the domain of job search in order to provide individuals more personalized recommendations of job listings based on their preferences. User profiles a re thus constructed based on the individual users preferences. On the other hand, user profiles a re helpful in improving the recommendations. In general, user profiles are structured based on the individual's preferences. User profiles can be represented in various ways, one such way is ontology which is the systematic categorization and representation of relationships between various entities within a domain. Ontologies has been widely used in the domain of e-commerce and medicine. In this paper, we use ontologies in the domain of personalized job recommendation, to model user profiles. The major objective of this paper is to provide an ontology based user profile for the domain of job recommendation. In particular, we identified suitable classes, attributes and relations that are specific to job recommendation system. In addition, we presented OWL representation of the proposed ontological model such that it can be reused by domain experts. © 2018 IEEE.