Researchers all have something in common, they write, and as much as they write, there comes a time they also need to look for additional information to add to the ones they have penned down, and sometimes, we just need to be sure of an idea, so we just want to confirm, and Google has been one of the most useful tools one can ever use for research and information sourcing.
But what do you think of information that may not be found on Google? Or sometimes, you may see little information on a subject, what do you do then? Well, you may have to visit a library and read some books before continuing your research, and that’s time wasting. What if you find the information? The fact still remains that not all who post contents online have extensive knowledge of these subjects, and that’s were Helix has been able to help.
Helix is a word processor plug-in that was created by Paul Burke and Neil Krishnan at this year’s Disrupt NY Hackathon. This software makes use of machine learning in the suggestion of citations and relevant research as you write. So, as you start with the topic and you start writing the contents, Helix scans the words, texts, and context and it pulls up recommended journal articles, news and Wikipedia pages. The recommended texts are displayed in a queue along the side of the writer’s main texts, so you can check it at a glance without moving your hands off the keyboards to the mouse in a bid to change windows.