A learning application to boost R & D
New ideas and opportunities
If a science, engineering or manufacturing business wants to trigger innovative thinking they need to make new connections, see things from a different perspective, look for what's missing as well as what's there.
When specialists such as R&D scientists and engineers search for new ideas, they often lead to incremental improvements rather than major step changes. It’s natural to remain close to what you know – far harder to step away and see radically different possibilities.
But if possible connections can be identified between one discipline and others that may have never been considered before, then big new ideas can take root. If a team knows much more about the research that others are conducting new possibilities for collaboration can start to take shape.
Researchers need a search engine that keeps them up-to-date with what is happening in their field. But they also need to see connections between search terms that, on the face of it, may not seem to be connected at all. This means searching articles and periodicals in such a way that apparently unrelated search items can be shown to have connections. It also means discovering sources where connections have been made that no-one has thought of at all.
The Figuringoutdata solution
Figuringoutdata.com have a solution that uses machine learning and AI techniques to make all of these connections possible.
Placing the Researcher in control
As Researchers use the application it builds a repository of everything they have found – as well as a history of all the search terms used.
It also tells them all about the sources accessed – how useful they have been for everyone who has accessed them, and their potential to be of use going forward.
1. Search Terms
The system remembers every search term used – by every user of the system. It tells the user how effective each search has been, with sources ranked according to their relevance.
2. Known data sources
As the list of data sources grows the system constantly evaluates the relevance of each given the search terms used. But is also offers up key terms and connections between them that have not yet appeared amongst the search terms used.
3. New search terms
When new search terms are added they are added to a repository that everyone can access. This allows different teams to have a clear understanding of everyones’ research interests and to then spot potential collaboration opportunities.
4. New data sources
Given the search terms use the system uses AI methods to discover and suggest new potential sources indicating the potential relevance of each given the search terms used so far.
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