Research Papers - Dept of Information Technology

Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/593

Browse

Filters

2014 - 20193

Advanced Search

Filter by

Settings

Has files: YesSubject: search.filters.subject.Sentiment Analysis

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    PublicationOpen Access
    Automated Customer Care Service System for Finance Companies
    (NCTM, 2014-12-16) Warnapura, A. K; Rajapaksha, D. S; Ranawaka, H. P; Fernando, P. S. S. J; Kasthuriarachchi, K. T. S; Wijendra, D
    In general, to obtain information about a product one should visit the company or contact the company via a phone call or some sort of a communication type, for example E-mail. Even so under normal circumstances the customer will receive the necessary information sent by a human being. There can be many disadvantages in this method. At the onset if a particular customer gives a phone call to the company the customer will have to wait for a considerable time. This is obvious because due to lack of human resources and phone lines there may be a question of customers waiting to get connected to the company line. On the other hand if a customer sends an email, the reply for the email will take time because the particular email should be perused by another human being at company in order to reply. These are few disadvantages apart from human errors that can happen. Ultimately as a result of above detrimental facts a faithful customer could get unsatisfied and lose confidence on a particular company. However, in the system that we are going to introduce, a particular customer can get any type of information in real time by the Aid of the Artificial Intelligence in the form of text/voice or E-mails. The advantages over the other method are that the customers will not have to wait for a reply, there are no space for human error and more importantly the company can use their human resources in other activities while the system takes care of the Customer care unit at least partially. Further, this system will be help to people who needs the immediate customer care assistance and will be able to get help by their own without involved human agent in another party for their assistance
  • Thumbnail Image
    PublicationOpen Access
    Mini Market: Information Technology Based Support Tool for Small and Medium Scale Enterprises in Sri Lanka
    (ICRD Publicatio, 2019-07) Thilakarathne, S; Herath, S; Rajapaksha, A; Karunasena, A
    Small and medium enterprises (SMEs) play a crucial role in developing countries such as Sri Lanka in growth of an economy. Recently online platforms are being extensively used by SMEs for both marketing and selling items. In a context of keen competition among the online selling platforms, sellers are increasingly feeling the pressure for improving their sales and marketing strategies. When investigating existing problems of SMEs, we were able to find they do not have proper guidance to improve their own business. Simply, the SMEs cannot identify their own marketing level among the other competitors, they haven't any suitable guidelines to identify how they can improve their own market and they have to use manual reports to get their own sales details for visualizing their marketing level where they waste their valuable time and money for visualizing sales market outcomes. In consideration of this, we propose a web system, that examines the effects of three categories in this system, i.e. Seller trustworthiness, analyze customer's emotions, feelings, thoughts, and opinions through Social media (Facebook) and sales prediction component. This system facilitates a multiple seller platform, where they can dynamically manage virtual shop inside this platform. It increases their stability and it will provide directions to overcome economic and unemployment barriers in our country. The results support our research hypotheses partially. The findings of this study are expected to provide some suggestions for sellers on promote and improve of their sales
  • Thumbnail Image
    PublicationEmbargo
    Stock Market Prediction Using Machine Learning Techniques
    (IEEE, 2019-12-05) Sirimevan, N; Mamalgaha, I. G. U. H; Jayasekara, C; Mayuran, Y. S; Jayawardena, C
    Predicting stock market prices is crucial subject at the present economy. Hence, the tendency of researchers towards new opportunities to predict the stock market has been increased. Researchers have found that, historical stock data and Search Engine Queries, social mood from user generated content in sources like Twitter, Web News has a predictive relationship to the future stock prices. Lack of information such as social mood was there in past studies and in this research, we discuss an effective method to analyze multiple information sources to fill the information gap and predict an accurate future value. For this, LSTM - RNN models were employed to analyze sperate sources and Ensembled method with Weighted Average and Differential Evolution technique were used for more accurate prediction of the stock prices. And highly accurate predictions were made to one-day, seven-days, 15-days and 30 days for the future. So that investors could gain an insight into what they are inventing for and the companies to track how well they will perform in the stock market.