SortingHat: a deep matching framework to match labeled concepts
Sumant Kulkarni, Srinath Srinivasa · International Conference on Management of Data · 2014
We report a framework called SortingHat to perform semantic matching between labeled concepts in a partially labeled corpora such as workflow data. We create a labeled term co-occurrence graph as the representative data-structure of the given corpus. The semantic matching between concepts is performed using a variant of random walk algorithm on the term co-occurrence graph. The SortingHat system takes a set of concepts as input and generates a semantically matching set of concepts for them. In this experiment, we use data from bug tracking system of a large enterprise to demonstrate the results.