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Searching semantically diverse paths

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Abstract

Location-Based Services are often used to find proximal Points of Interest (PoIs)—e.g., nearby restaurants and museums, police stations, hospitals, etc.—in a plethora of applications. An important recently addressed variant of the problem not only considers the distance/proximity aspect, but also desires semantically diverse locations in the answer-set. For instance, rather than picking several close-by attractions with similar features—e.g., restaurants with similar menus; museums with similar art exhibitions—a tourist may be more interested in a result set that could potentially provide more diverse types of experiences, for as long as they are within an acceptable distance from a given (current) location. Towards that goal, in this work we propose a novel approach to efficiently retrieve a path that will maximize the semantic diversity of the visited PoIs that are within distance limits along a given road network. Our approach allows to specify both a start and terminal location to return a (non-necessarily shortest) path that maximizes diversity rather than only minimizing travel cost, thus providing ample applications in tourist route recommendation systems. We introduce a novel indexing structure—the Diversity Aggregated R-tree, based on which we devise efficient algorithms to generate the answer-set—i.e., the recommended locations among a set of given PoIs—relying on a greedy searching strategy. Our experimental evaluations conducted on real datasets demonstrate the benefits of the proposed methodology over the baseline alternative approaches.

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Acknowledgements

Dr. Züfle is supported by National Science Foundation AitF Grant CCF-1637541. Dr. Trajcevski is supported by National Science Foundation Grant SWIFT 203024.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa, 50011, USA

    Xu Teng & Goce Trajcevski

  2. Department of Geography and Geoinformation Science, George Mason University, Fairfax, Virginia, 22030, USA

    Andreas Züfle

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  1. Xu Teng
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  2. Goce Trajcevski
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  3. Andreas Züfle
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Correspondence to Xu Teng, Goce Trajcevski or Andreas Züfle.

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Teng, X., Trajcevski, G. & Züfle, A. Searching semantically diverse paths. Distrib Parallel Databases 41, 603–638 (2023). https://doi.org/10.1007/s10619-022-07413-x

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