Faculty of Computing

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    SalFix: Solutions for Small Businesses Using Artificial Intelligence and Machine Learning
    (2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Perera, T.; Kuganandamurthy, L.; Ameen, T.; Dassanayake, T.; Ganegoda, D.
    Every large organization was a small business before. There are many businesses starting every day. Most of them are small businesses. Managing a business is always a challenge. The owners face lots of challenges when they engage with a business. Small business owners do not have enough knowledge about advertising or promoting a product. New owners do not know the trendiest product at present, and they need to know to sell which product to be profitable. L ack o f communication with the customers will impact the customer base. These are the main problems that owners face. By introducing SalFix, these challenges can be conquered. SalFix is a web application that is suitable for current owners and new owners. SalFix uses Artificial I ntelligence t o g enerate a utomated a d i mages, predict what will happen to the business next year, predict which product is the trendiest. To improve customer communication, SalFix is embedded with a chatbot plugin that can be integrated into the small business’s website. SalFix can perform a SWOT analysis as well. Owners can use SalFix to fix t heir s ales and boost their income. SalFix is a yearly subscription service and will provide more accurate results.
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    Usability and user experience towards an experience economy
    (Faculty of Graduate Studies and Research, 2017-01-26) Weerawarna, N.T.; Abeysiri, L.
    Technological advances of the modern day have helped combine usability and user experience. Both factors contribute heavily towards a user's satisfaction which is essential in an `experience economy'. Proceeding with identified literature related to `usability' and `user experience', this research attempts to identify whether there is a significant impact on five different factors related to usability and user experience and benchmark them to suit user's overall satisfaction. The methodology for the research followed the identification of the theory involved in terms of five factors with Web application use in terms of user's satisfaction. A structured questionnaire based on the five factors was next drawn up and used on a sample of 88 Web application users. The collected data was analysed using a statistical tool. The results were further validated using a primary data collection with 20 Web application users. A structured interview process was used for the purpose. The use of a common factor `satisfaction', helped reveal that usability and user satisfaction only were affected as against the other three variables. Perhaps, a more detailed study may reveal the absorption of the other variables as related to user satisfaction.