Research Papers - Dept of Information Technology

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    eGaz: Enhanced Search Engine for Gazette Publications
    (IEEE, 2022-07-18) Mendis, M. C. P; Perera, M. S. M; Karunaratne, J. M. P. D; Silva, K. K. S; Haddela, P. S; Gunarathne, D. A
    A government gazette is a periodical distribution that has been approved to distribute public or legitimate takes note. Presently, governments gazettes are published in the official website with the facility of downloading the individual files in portable document format. Even though these gazettes are categorized into a few types, individual gazettes contain diverse amount of material from various sectors of the government making it stiffer to the reader to search for their preferred apprises without reading the complete file. To address this problem as a possible convenient solution, Enhanced Search Engine for Gazette Publications was developed. The system is able to scrape gazette files from the official website, which is followed by a progression of text extraction, summarizing and clustering the extracted data and hoard them in a distributed system. With the use of the Content Search Engine, user could loop through any material issued over gazettes which would bring up filtered results from the extracted data. Similarly, users can read summarized reports of advertisements on job vacancies, examination details and results of examinations and could even filter them by relevant departments.
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    PROBEXPERT: An Enhanced Q&A Platform for Reducing Time Spent on Learning and Finding Answers
    (IEEE, 2022-07-18) Thennakoon, K; Ekanayake, D; Marapana, T; Ranasinghe, A; Wijendra, D. R; Gamage, A
    The World Wide Web contains a wide range of material from a variety of fields. However, when concerns towards the computer science domain, information users find on the internet may not be up-to-date due to the rapid pace of change and having to spend less time on the internet for researching and debugging tasks is an added luxury. Having an expertise level while providing answers through a platform is convenient for users, yet when a user signs into a platform, the user must start from the beginning, regardless of the level of competence in the field. Moreover, not having a proper way to evaluate the existing programming knowledge is another obstacle. To address mentioned complications, researchers of this paper have introduced a new e-learning platform- ‘ProbExpert’. The platform has been constructed with machine learning and deep learning approaches such as NLP, keyword extraction, semantic information analysis, cosine similarity, and information summarization. With aforesaid technologies, ProbExpert provides systems in automated answering, optimized answer generation, structured question-based quiz evaluation together with a fully automated portfolio generation with a novel user ranking algorithm based on the bell curve.
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    User-friendly Enhanced Machine Learning-based Railway Management System for Sri Lanka
    (IEEE, 2021-12-06) Mihiranga, G.L.V; Weerasooriya, W. K. M; Palliyaguruge, T. L. P; Gunasekera, P. N. G; Gamage, M. P; Kumari, S. P. K
    The railway service is a convenient and low-cost transport method in Sri Lanka, widely employed by both local and foreign passengers. Major railway lines in Sri Lanka cover unique and very different areas in the country. For example, the Northern province's weather and geography conditions significantly differ from Southern or Central provinces. Majority of the tourists lack understanding in identifying appropriate or attractive places that best suits them, close by to the Railway Stations. Therefore, a passenger needs to spend more time identifying their railway tour destinations. When passengers are booking tickets, even though they are able to reserve seats beforehand, they are unable to reserve a specific seat. Also, there is no process to identify the most suitable seat for them amidst many other travelers, especially if they are travelling alone. Considering the aforementioned, authors propose a more innovative and user-friendly system for the Railway Department of Sri Lanka. Depending on various passenger attributes the system is capable of suggesting a travel plan with railway lines which cover most suitable destination suggestions; identifying the best seats with a relaxing atmosphere; providing an interactive chatbot to satisfy user queries on specific location information; and facility for 24×7 user interaction. A travel plan can save passengers time and allows them to identify the desired railway line and relevant attractions without much hassle. And they are saved of an unpleasant experience through the suggestion of the best seating location. Machine Learning and Deep Learning technologies are used in developing the proposed system.
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    Plagiarism Detection Tool for Enhanced Entity-Relationship Diagrams
    (IEEE, 2021-12-01) Dahanayake, H; Samarajeewa, D; Jayathilake, A; Bandara, D; Karunasena, A; Weerasinghe, L
    Plagiarism is presenting someone else’s work as one’s own work without giving credit to the original owner. Recently, plagiarism has become a serious issue in the fields of Education and Technology. To address this issue, many systems have been implemented to detect plagiarism. However, most of them are designed to deal with plagiarism of text content. Detecting plagiarism in figures and diagrams is equally important. Although there is research done on detecting plagiarism in images and flow charts, there is no research done on detecting plagiarism in more complex diagrams such as Enhanced Entity-Relationship (EER) diagrams. This paper presents a methodology to detect plagiarism in EER diagrams using Deep Neural Networks (DNN), image processing techniques, Optical Character Recognition (OCR) techniques, and text similarity detection algorithms. Since the students are aware of the existence of a plagiarism detecting tool, it will encourage the students to do work on their own and it will reduce exam offenses. The similarity report can be presented as proof to the offenders who are not accepting that they have plagiarized others' work. Using the proposed system, the EER diagram plagiarism can be detected much faster and accurately. Therefore, the efficiency of marking examinations will be increased. The final outcome of the system will be a similarity report including the plagiarized content in the compared EER diagrams.
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    Enhanced Tokenizer for Sinhala Language
    (IEEE, 2019-10-08) Senanayake, S. Y; Kariyawasam, K. T. P. M; Haddela, P. S
    Tokenization process plays a prominent role in natural language processing (NLP) applications. It chops the content into the smallest meaningful units. However, there is a limited number of tokenization approaches for Sinhala language. Standard analyzer in apache software library and natural language toolkit (NLTK) are the main existing approaches to tokenize Sinhala language content. Since these are language independent, there are some limitations when it applies to Sinhala. Our proposed Sinhala tokenizer is mainly focusing on punctuation-based tokenization. It precisely tokenizes the content by identifying the use case of punctuation mark. In our research, we have proved that our punctuation-based tokenization approach outperforms the word tokenization in existing approaches.