Browsing by Author "Kirindage, G"

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Automatic Sinhala News Classification Approach for News Platforms
(Institute of Electrical and Electronics Engineers Inc., 2020-12-18) Kirindage, G; Godewithana, N
Because of generating various news articles in large scale, online sources moved into an automatic categorization mechanism. This research has been conducted using LDA topic modeling approach and using other classification algorithms to establish a news categorization solution. Sinhala news websites have only few news categories and do not have any relationships or hierarchies between the categories. Therefore, some users require to search manually and find the necessary articles which are in those categories. Purpose of this study is to build a news categorization model with categorization hierarchies for Sinhala news articles. The goals of the models are to identify the most suitable news category for a related news article and develop hierarchies using generated news categories and assign the news articles according to the hierarchical structure. The final experiments and evaluations show that the solution performs well to solve the automatic categorization problem in Sinhala news platforms.
Embargo
Intelligent Hybrid Chatbot Solution for Archaeological Sites Tracking
(IEEE, 2021-02-26) Godewithana, N; Kirindage, G
Not only in the country like Sri Lanka, but also most of the countries have numerous historically valued places and monuments that provide great survival and civilization history. While searching information about those places, there exists a lack of information and trusted information sources. Even though some information is available, it does not include the convenient and efficient ways to retrieve the information. The proposed system contributes a solution to the aforementioned problem with Artificial Intelligence [AI] & Deep Learning [DL] concepts. The proposed chatbot solution helps to enhance the user experience while retrieving the available information about the archeological places from the system. It can automate the searching task by enabling a methodology for chatting with the user via a conversational interface. The proposed voice detection module, natural language processing model and the dialog management model leverages a higher accuracy rate and it will showcase the power of search assistants. Furthermore, it shows how it can be an alternative to the usage of the application and enhance the user experience without any hesitation.