
doi: 10.3233/isu-160793
Information is only valuable when it can be found. It is relatively easy to find information that we know exists; you just need to know what you want to find, where to look for it, and how to express yourself. It might require a little effort to find it, but this work is usually rewarded. But, what if you’re looking to acquire new knowledge or want to search for unusual findings? Normally you start with what you know and learn as you go and in the end arrive at some conclusion, but how do you know you have found all relevant information and how do you know how this information is connected to the rest of the information space? The answer up until now is that you don’t, and to get the big picture you would have to aggregate your results manually. Microsoft has studied search behavior and a big part of the daily searches are exploratory in nature, where the users aren’t sure what they want to find and are struggling while trying. The Etsimo Visual Discovery engine offers an alternative, or complement, to lookup searching by providing a transparent and user-driven way to visually navigate the information space, learn as you go, and find relevant information.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
