On personalized and sequenced route planning

Dai, Jian; Liu, Chengfei; Xu, Jiajie; Ding, Zhiming

doi:10.1007/s11280-015-0352-2

Cited by 26 publications

(16 citation statements)

References 17 publications

(40 reference statements)

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“…In [30], the cosine similarity algorithm was adopted for providing sightseeing routes of high cultural interest in Japan. In [31], a 3-stage framework targets on satisfying user preferences for visiting selected POI by generating an optimal personalized route. A tour route planning model was proposed [32] targeting to maximize the tourism experience within a specific budget and time frame by satisfying real-time requirements of Web or mobile users.…”

Section: Related Work For Route Planning Modelingmentioning

confidence: 99%

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A route planning framework for smart wearable assistive navigation systems

Ntakolia

Iakovidis

2021

SN Appl. Sci.

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Route planning (RP) enables individuals to navigate in unfamiliar environments. Current RP methodologies generate routes that optimize criteria relevant to the traveling distance or time, whereas most of them do not consider personal preferences or needs. Also, most of the current smart wearable assistive navigation systems offer limited support to individuals with disabilities by providing obstacle avoidance instructions, but often neglecting their special requirements with respect to the route quality. Motivated by the mobility needs of such individuals, this study proposes a novel RP framework for assistive navigation that copes these open issues. The framework is based on a novel mixed 0–1 integer nonlinear programming model for solving the RP problem with constraints originating from the needs of individuals with disabilities; unlike previous models, it minimizes: (1) the collision risk with obstacles within a path by prioritizing the safer paths; (2) the walking time; (3) the number of turns by constructing smooth paths, and (4) the loss of cultural interest by penalizing multiple crossovers of the same paths, while satisfying user preferences, such as points of interest to visit and a desired tour duration. The proposed framework is applied for the development of a system module for safe navigation of visually impaired individuals (VIIs) in outdoor cultural spaces. The module is evaluated in a variety of navigation scenarios with different parameters. The results demonstrate the comparative advantage of our RP model over relevant state-of-the-art models, by generating safer and more convenient routes for the VIIs.

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Section: Related Work For Route Planning Modelingmentioning

confidence: 99%

“…Maximization of the corresponding score function such as the feasible solution query with respect to distance [31] Ranged-R-Tree Query process…”

Section: Minimum Cost Hamiltonian Cycle Algorithmmentioning

confidence: 99%

A route planning framework for smart wearable assistive navigation systems

Ntakolia

Iakovidis

2021

SN Appl. Sci.

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“…Yuya Sasaki et al [22] propose the skyline sequenced route (SkySR) query, which is similar to OSR query, the difference is that SkySR query does not strictly obey the passing categories, but adopts the similar categories using a semantic hierarchy. Jian Dai et al [8] propose the Personalized and Sequenced Route (PSR) query, which considers both the sequenced constraint and personalized category preferences, and develop a framework to solve the query. Similar to [8], Francesco Lettich et al [12] propose the Trade-Off Aware Sequenced Routing (TASeR) query, which extends the OSR query with a POI cost (that is, each POI has a visiting cost), and an approach using the linear skyline paradigm to process the query.…”

Section: Single User Queriesmentioning

confidence: 99%

Querying Optimal Routes for Group Meetup

et al. 2021

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Motivated by location-based social networks which allow people to access location-based services as a group, we study a novel variant of optimal sequenced route (OSR) queries, optimal sequenced route for group meetup (OSR-G) queries. OSR-G query aims to find the optimal meeting POI (point of interest) such that the maximum users’ route distance to the meeting POI is minimized after each user visits a number of POIs of specific categories (e.g., gas stations, restaurants, and shopping malls) in a particular order. To process OSR-G queries, we first propose an OSR-Based (OSRB) algorithm as our baseline, which examines every POI in the meeting category and utilizes existing OSR (called E-OSR) algorithm to compute the optimal route for each user to the meeting POI. To address the shortcomings (i.e., requiring to examine every POI in the meeting category) of OSRB, we propose an upper bound based filtering algorithm, called circle filtering (CF) algorithm, which exploits the circle property to filter the unpromising meeting POIs. In addition, we propose a lower bound based pruning (LBP) algorithm, namely LBP-SP which exploits a shortest path lower bound to prune the unqualified meeting POIs to reduce the search space. Furthermore, we develop an approximate algorithm, namely APS, to accelerate OSR-G queries with a good approximation ratio. Finally the experimental results show that both CF and LBP-SP outperform the OSRB algorithm and have high pruning rates. Moreover, the proposed approximate algorithm runs faster than the exact OSR-G algorithms and has a good approximation ratio.

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“…Among them, one of the popular issues is the path/route planning in a point-of-interest (POI) network [1,2]. The users of the LBS often want to find short routes that pass through multiple POIs; consequently, developing trip planning queries that can find the shortest routes that passed through user-specified categories has attracted considerable attention [3,4]. While the problem of computing the optimal route has been extensively studied and many efficient techniques have been developed over the past several decades, most of the past studies on route planning focused on origindestination route planning and did not consider the user's specific requirements.…”

Section: Introductionmentioning

confidence: 99%

“…(1) We introduce a semantic similarity to the route search query, which allows us to search for routes flexibly (2) We propose the top-k optimal route based on semantic perception (KOR-SP), which finds all preferred routes related to keyword with semantic perception (3) We propose a method to find the -th nearest neighbor based on semantic perception (4) We use real-world POI datasets to test and prove the superiority of the algorithm.…”

Section: Introductionmentioning

confidence: 99%

Semantic‐Aware Top‐k Multirequest Optimal Route

et al. 2019

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In recent years, research on location-based services has received a lot of interest, in both industry and academic aspects, due to a wide range of potential applications. Among them, one of the active topic areas is the route planning on a point-of-interest (POI) network. We study the top-k optimal routes querying on large, general graphs where the edge weights may not satisfy the triangle inequality. The query strives to find the top-k optimal routes from a given source, which must visit a number of vertices with all the services that the user needs. Existing POI query methods mainly focus on the textual similarities and ignore the semantic understanding of keywords in spatial objects and queries. To address this problem, this paper studies the semantic similarity of POI keyword searching in the route. Another problem is that most of the previous studies consider that a POI belongs to a category, and they do not consider that a POI may provide various kinds of services even in the same category. So, we propose a novel top-k optimal route planning algorithm based on semantic perception (KOR-SP). In KOR-SP, we define a dominance relationship between two partially explored routes which leads to a smaller searching space and consider the semantic similarity of keywords and the number of single POI’s services. We use an efficient label indexing technique for the shortest path queries to further improve efficiency. Finally, we perform an extensive experimental evaluation on multiple real-world graphs to demonstrate that the proposed methods deliver excellent performance.

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On personalized and sequenced route planning

Cited by 26 publications

References 17 publications

A route planning framework for smart wearable assistive navigation systems

A route planning framework for smart wearable assistive navigation systems

Querying Optimal Routes for Group Meetup

Semantic‐Aware Top‐k Multirequest Optimal Route

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