Figure 1.

Inference analytics. (A) Data analytics typically analyze large datasets to draw inferences; these inferences are usually used directly; the inferences may be evaluated with relatively small investment of resources or through crowdsourcing. (B) In areas such as biology, it is desirable that data analytics is followed by inference analytics; these algorithms would analyze the large number of data analytic inferences and re-ranking them by various criteria to aid the users in selecting which inference to pursue. The work presented here corresponds to inference analytics for “scientific impact prediction” criterion.

Ganapathiraju and Orii GigaScience 2013 2:11   doi:10.1186/2047-217X-2-11
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