Prof. P Krishna Reddy and his students P Revanth Rathan and Anirban Mondal published a paper on A framework for discovering popular paths using transactional modeling and pattern mining in Distributed and Parallel Databases, Springer in September.

Research work as explained by the authors Prof. P Krishna Reddy, P Revanth Rathan and Anirban Mondal: While the problems of finding the shortest path and k-shortest paths have been extensively researched, the research community has been shifting its focus towards discovering  and  identifying  paths  based  on  user  preferences.  Since  users  naturally  follow  some of the paths more than other paths, the popularity of a given path often reflects such  user  preferences.  Given  a  set  of  user  traversals  in  a  road  network  and  a  set  of  paths between a given source and destination pair, we address the problem of performing  top-k  ranking  of  the  paths  in  that  set  based  on  path  popularity.  In  this  paper,  we  introduce a new model for computing the popularity scores of paths. Our main contributions are threefold. First, we propose a framework for modeling user traversals in a  road network as transactions. Second, we present an approach for efficiently computing the popularity score of any path based on the itemsets extracted from the transactions using pattern mining techniques. Third, we conducted an extensive performance evaluation with two real datasets to demonstrate the effectiveness of the proposed scheme.