Abstract Visually impaired programmers have been included into programming industry since its very beginning and they were able to perform their jobs without difficulties. Graphical user interfaces and point and click method of instructing computers have created many difficulties for visually impaired programming professionals. Visually impaired have interest in programming just as everyone else and the means of their inclusion in... Visually impaired programmers have been included into programming industry since its very beginning and they were able to perform their jobs without difficulties. Graphical user interfaces and point and click method of instructing computers have created many difficulties for visually impaired programming professionals. Visually impaired have interest in programming just as everyone else and the means of their inclusion in overall software development process are important issues that need to be resolved. One of disadvantages for visually impaired is the lack of assistive technology that would enable them to design and create graphical user interfaces. In this paper the GUIDL (Graphical User Interface Description Language) system that is aimed to resolve the mentioned issues is presented and discussed. Read More Read Less

Abstract This paper leverages cloud-based machine learning platform to implement an item-based recommendation system for an e-commerce application. The solution is based on Prediction IO platform, which offers a fullstack architecture based on MongoDB database, Hadoop framework for distributed processing, Apache Mahout scalable machine learning library, and RESTful API. We implemented an item-based recommendation engine for product suggestions in an online... This paper leverages cloud-based machine learning platform to implement an item-based recommendation system for an e-commerce application. The solution is based on Prediction IO platform, which offers a fullstack architecture based on MongoDB database, Hadoop framework for distributed processing, Apache Mahout scalable machine learning library, and RESTful API. We implemented an item-based recommendation engine for product suggestions in an online retail store using realworld data. Preliminary results are quite promising achieving Mean Average Precision of 6 %. Read More Read Less