Title
A framework for discovering popular paths using transactional modeling and pattern mining
Abstract
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.
Year
DOI
Venue
2022
10.1007/s10619-021-07366-7
Distributed and Parallel Databases
Keywords
DocType
Volume
Popular paths, Transactional modeling, Pattern mining, Road networks
Journal
40
Issue
ISSN
Citations 
1
0926-8782
0
PageRank 
References 
Authors
0.34
9
3
Name
Order
Citations
PageRank
P. Revanth Rathan100.34
P. Krishna Reddy200.34
Anirban Mondal338631.29