Research Publications
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Publication Embargo Pre-Interview Reviewer Using Natural Language Processing for Software Engineers in The IT Industry : Pre-interview reviewer(IEEE, 2023-03-28) Shaman, M.A.M.; Samarasinghe, S.M.; Tharinda, D; Gamage, D.C.; Gamage, AThe internet use to look for work has increased dramatically in recent years, and the number of job applicants has also increased. Numerous conventional websites promote online job postings using graphical and writeable ways. But the respective websites do not support HR (Human resources) in selecting the most suitable person from the candidates applying for the individual jobs. So, The HR department, faced with a large pool of applicants, faces the task of selecting the best one. To address this problem, we've developed a new web tool called "Pre-interview reviewer" that can be used by any company in the IT sector to quickly and easily narrow down the pool of applicants for software engineering roles. We use various methods to narrow down the pool of potential hires. We are training an algorithm to identify the best candidates by assessing the Curriculum Vitae (CV), providing selected questionaries relevant to the HR-provided job description requirement, and using leadership and teamwork skills to analyze questions. Using this system, the companies can utilize the pre-interview sections. Then time consummation will happen. Here, we take a natural language processing-based approach to creating a web app and web-dev languages, among others. In the end, this approach is meant to take advantage of the intricate nature of company recruitment.Publication Embargo Recommendation system based on Tamil-English code-mixed text analysis(Institute of Electrical and Electronics Engineers, 2022-10-15) Vijayakumar, S; Murugaiah, G; Sivanesan, J; Archchana, K; Tissera, W; Vidhanaarachchi, SThe cinema industry has always been popular since its inception many years ago and is a preferred pastime of many people. It can be observed that even though online movie applications are popular in multilingual society, English is the preferred language. Naturally, people of other languages mix their native language with English during communications resulting in an abundance of multilingual data called code-mixed data, available in today's world. This research focuses on the movie recommendation system whose primary objective is to make a recommender system through Natural Language Processing (NLP) Tools for Tamil-English Code-mixed (Tanglish) Comments. Our recommendation system will be a filtering scheme whose primary objective is to predict a viewer's rating or preference towards a movie or web series.