Engineering Generalized Shortest Path queries

Rice, Michael N.; Tsotras, Vassilis J.

doi:10.1109/icde.2013.6544888

Cited by 18 publications

(12 citation statements)

References 8 publications

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“…Based on these, they use Maximum Probability Product algorithm to mine the most popular route. Compared to [5], [19] considers the uncertainty of trajectory to get the popular route. Both of them ignore that the route distance are also very important, when people are choosing the route they want.…”

Section: B Trajectory Miningmentioning

confidence: 99%

TORD Problem and Its Solution Based on Big Trajectories Data

Yin

2016

IEEE Trans. Intell. Transport. Syst.

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Identifying a preferable route is an important problem in location-based service. A user may want to find "an optimal route such that it passes by mall, restaurant, and bank, meanwhile go through bank before mall, and arrive at the restaurant at mealtime." However, none of the algorithms in the existing work on route planning can be used to answer such queries that exist in real life. Motivated by this, we define the problem of temporal-sensitive optimal route discovery (TORD), which is an NP-hard problem. Since the rise of GPS-equipped mobile devices has led to the emergence of big trajectory data, we propose a hybrid evaluation indicator of routes called preference combined by the distance from the road network and popularity from trajectories. To achieve this goal, we first develop an improved compact minimum bound rectangle algorithm to get the association between trajectory data and road network, which can update the association conveniently for new trajectories. Then, we construct a two-layer preference network that is used for mining the preference and travel time. Finally, we devise three approximation algorithms to answer TORD queries. The results of empirical studies show that all the proposed algorithms are capable of answering TORD queries efficiently.Index Terms-Big trajectory data, trajectory data mining, spatio-temporal data mining, intelligent transportation, route planning.

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Section: B Trajectory Miningmentioning

confidence: 99%

TORD Problem and Its Solution Based on Big Trajectories Data

Yin

2016

IEEE Trans. Intell. Transport. Syst.

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“…Table I clearly shows that this paper is the first comprehensive study for addressing the sequenced route problem on general graphs, with specific category orders, and k ≥ 1, i.e., the top-k optimal sequenced route (KOSR) problem. Table I. CATEGORIZATION OF SEQUENCED ROUTE QUERIES Euclidean Graphs General Graphs k = 1 Specific order: [32] Arbitrary order: [8], [26], [27] Specific order: [29], [32], [33] Arbitrary order: [7], [30] k ≥ 1 Specific order: [22], [23], [31] Arbitrary order:∅ Specific order: This paper Arbitrary order:∅…”

Section: Related Workmentioning

confidence: 99%

“…2) GSP: Another state-of-the-art method, namely GSP, for the optimal sequenced route within graph is proposed in [29], in which, a dynamic programming solution is formulated as follows:…”

Section: ) Pnementioning

confidence: 99%

“…Since no categorical information is associated with the vertices in these graphs, we generate categories for the vertices using both uniform and zipfian distributions. In particular, we follow [29] to generate uniform distributions. We fix the number of vertices in each category with parameter |C i |, and then uniformly assign a category to vertices.…”

Section: A Experimental Setupmentioning

confidence: 99%

“…Optimal sequenced route (OSR) querying [32], [33], a.k.a., generalized shortest path querying [29], aims at finding a route with minimum total cost (e.g., travel distance or travel time), passing through a number of vertex categories (e.g., restaurants, banks, gas stations) in a particular order (e.g., visiting banks before restaurants). This problem has many practical applications in route planing [14], [19], crisis management, supply chain management, video surveillance, mobility-as-aservice [13], and logistics [29], [32]. However, it is often the case that the optimal sequenced route with the minimum total cost may not be the best choice for all users since different users may have different personal preferences [10], [28], [36].…”

Section: Introductionmentioning

confidence: 99%

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Finding Top-k Optimal Sequenced Routes

Liu

Jin

Yang

et al. 2018

2018 IEEE 34th International Conference on Data Engineering (ICDE)

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Motivated by many practical applications in logistics and mobility-as-a-service, we study the top-k optimal sequenced routes (KOSR) querying on large, general graphs where the edge weights may not satisfy the triangle inequality, e.g., road network graphs with travel times as edge weights. The KOSR querying strives to find the top-k optimal routes (i.e., with the top-k minimal total costs) from a given source to a given destination, which must visit a number of vertices with specific vertex categories (e.g., gas stations, restaurants, and shopping malls) in a particular order (e.g., visiting gas stations before restaurants and then shopping malls).To efficiently find the top-k optimal sequenced routes, we propose two algorithms PruningKOSR and StarKOSR. In Prun-ingKOSR, we define a dominance relationship between two partially-explored routes. The partially-explored routes that can be dominated by other partially-explored routes are postponed being extended, which leads to a smaller searching space and thus improves efficiency. In StarKOSR, we further improve the efficiency by extending routes in an A * manner. With the help of a judiciously designed heuristic estimation that works for general graphs, the cost of partially explored routes to the destination can be estimated such that the qualified complete routes can be found early. In addition, we demonstrate the high extensibility of the proposed algorithms by incorporating Hop Labeling, an effective label indexing technique for shortest path queries, to further improve efficiency. Extensive experiments on multiple real-world graphs demonstrate that the proposed methods significantly outperform the baseline method. Furthermore, when k = 1, StarKOSR also outperforms the state-of-the-art method for the optimal sequenced route queries. This is a full version of "Finding Top-k Optimal Sequenced Routes" [20], to appear in IEEE ICDE 2018.

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