Keenious - Recommendation Engine Research Tool

Everyone who is or has been a student knows of the struggle when it comes to finding relevant research articles and references when writing their essays. Countless hours are spent going through different database websites, web searches and asking advisors for help. We at Keenious want to alleviate the students and researchers from around the world from this time-consuming exercise by helping them find exactly what they need to support their essays and articles, freeing them to further expand the world of academics. There is an abundance of scientific research available online, and we want it to be easier to find and use. With current research tools, students and researchers alike are spending ever more time finding the most relevant sources for their research. They also require users to have extensive knowledge of the topic and the ability to formulate the right keywords in order to find the best texts and sources. The goal of this SME project is for Keenious to provide a simpler and more elegant solution so that anyone, no matter their technological proficiency, can access the world’s research. After over a year of development, Keenious recently had a successful soft launch. Keenious is now being used by people all over the world, successfully helping them write better papers and assignments. Our ads have high click-through rates, and our recurring users are using it regularly. We’re also experiencing organic growth and getting very encouraging feedback. The Keenious innovation is a recommendation engine, available in both Microsoft Word and Google Docs, that helps students and researchers more easily explore and find scientific knowledge. The recommendation engine is built upon machine learning, and analyzes the user’s text input, and then suggests relevant research papers from a database of over 65 million research articles. This is done in just a few seconds, hugely increasing the productivity of whoever uses it.