PROJECT TITLE :
Efficient Clue-based Route Search on Road Networks - 2017
With the advances in geo-positioning technologies and placement-based mostly services, it's nowadays quite common for road networks to possess textual contents on the vertices. Previous work on identifying an optimal route that covers a sequence of query keywords has been studied lately. However, in several practical eventualities, an optimal route may not forever be fascinating. For example, a personalised route query is issued by providing some clues that describe the spatial context between PoIs along the route, where the result will be way from the optimal one. Therefore, during this paper, we investigate the matter of clue-primarily based route search (CRS), that allows a user to produce clues on keywords and spatial relationships. First, we propose a greedy algorithm and a dynamic programming algorithm as baselines. To improve potency, we have a tendency to develop a branch-and-sure algorithm that prunes unnecessary vertices in question processing. So as to quickly locate candidate, we have a tendency to propose an AB-tree that stores both the gap and keyword info in tree structure. To additional scale back the index size, we construct a PB-tree by utilizing the virtue of two-hop label index to pinpoint the candidate. Extensive experiments are conducted and verify the superiority of our algorithms and index structures.
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