2. Conference Papers

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    Currency recognition system using image processing
    (2018) 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.
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    Ontologies to Model User Profiles in Personalized Job Recommendation
    (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.