Browsing by Author "Hindakaraldeniya, TM"

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Dominant color palette extraction in resumes using the new color pixel quantifier algorithm
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa., 2023-12-07) Perera, NN; Warusawithana, SP; Weerasinghe, RL; Hindakaraldeniya, TM; Ganegoda, GU; Piyatilake, ITS; Thalagala, PD; Ganegoda, GU; Thanuja, ALARR; Dharmarathna, P
In the realm of resume analysis and enhancement, the extraction of dominant color palettes plays a pivotal role in assessing the visual impact of resumes. Existing methods designed for images with extensive color ranges have proven to be suboptimal when applied to the distinct context of resumes, which inherently possess a limited color palette. This paper introduces a novel approach that addresses this challenge effectively and efficiently. By minimizing the time required for palette extraction without compromising accuracy, the proposed method offers a practical solution for resume feedback systems. It is important to clarify that this research neither rejects nor supports existing methods; instead, it presents an alternative, tailor-made solution for resume analysis. In summary, this paper sets a promising precedent for more streamlined and functional dominant color palette extraction methods in the context of resumes, promising advancements in resume analysis and improvement.
item: Conference-Full-text
Layout aware resume parsing using nlp and rule-based techniques
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa., 2023-12-07) Warusawithana, SP; Perera, NN; Weerasinghe, RL; Hindakaraldeniya, TM; Ganegoda, GU; Piyatilake, ITS; Thalagala, PD; Ganegoda, GU; Thanuja, ALARR; Dharmarathna, P
As a result of the rapid development seen in the field of IT, there has been a surge in the number of students choosing IT field related degrees in recent years When those students try to secure job a better fob position in the field of IT, resume plays a vital role as it is often the first document a recruiter will see in the recruitment process. Therefore, this paper introduces a layout aware resume parsing system based on NLP and rule-based techniques to extract the section wise text content from the resume. This output can be used as the input for the resume content scoring model as a resume content review system to get feedback for the resume. When comparing existing methods with the proposed system, the layout of the resume would be considered in the proposed system, and it would extract content for each section. In addition to that, the proposed system would extract all the text content, but existing systems only extract the entities. In summary, this study is focused on developing a layout aware resume parsing system based on NLP and rule-based techniques to extract the section wise text content from the resume for an accurate resume review.
item: Conference-Full-text
Resume content scoring and improvement suggestions using nlp and rule-based techniques
(Information Technology Research Unit, Faculty of Information Technology, University of Moratuwa., 2023-12-07) Weerasinghe, RL; Perera, NN; Warusawithana, SP; Hindakaraldeniya, TM; Ganegoda, GU; Piyatilake, ITS; Thalagala, PD; Ganegoda, GU; Thanuja, ALARR; Dharmarathna, P
Having a proper resume is very important for undergraduates or fresh graduates to find their dream job. But most of them find it difficult to prepare their resume properly by themselves. It often needs a third party to review the resume to identify missing parts and content improvements of the resume because most of the time candidates make some mistakes. When it comes to resume review systems, most of the systems are based on the recruiter perspective which does not provide any insights for the candidate to improve their resumes. Hence, it is helpful if a proper resume content reviewer is there for candidates to analyze their resumes. This study is focused on developing a model to resume content scoring and suggest missing content based on NLP and rule-based techniques. Two separate approaches were developed and tested for the proposed system and then the comparison of those approaches were carried out through this study.