Spatial Object Recommendation with Hints: When Spatial Granularity Matters

SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval Virtual Event China July, 2020, pp. 781-790, 2020.

Cited by: 0|Bibtex|Views95|DOI:https://doi.org/10.1145/3397271.3401090
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Abstract:

Existing spatial object recommendation algorithms generally treat objects identically when ranking them. However, spatial objects often cover different levels of spatial granularity and thereby are heterogeneous. For example, one user may prefer to be recommended a region (say Manhattan), while another user might prefer a venue (say a res...More

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