GroupFinder: A New Approach to Top-K Point-of-Interest Group Retrieval
Kenneth S. Bøgh, Anders Skovsgaard, Christian S. Jensen · 2013
The notion of point-of-interest (PoI) has existed since paper road maps began to include markings of useful places such as gas sta-tions, hotels, and tourist attractions. With the introduction of geo-positioned mobile devices such as smartphones and mapping ser-vices such as Google Maps, the retrieval of PoIs relevant to a user’s intent has became a problem of automated spatio-textual informa-tion retrieval. Over the last several years, substantial research has gone into the invention of functionality and efficient implementa-tions for retrieving nearby PoIs. However, with a couple of excep-tions existing proposals retrieve results at single-PoI granularity. We assume that a mobile device user issues queries consisting of keywords and an automatically supplied geo-position, and we tar-get the common case where the user wishes to find nearby groups of PoIs that are relevant to the keywords. Such groups are relevant to users who wish to conveniently explore several options before mak-ing a decision such as to purchase a specific product. Specifically, we demonstrate a practical proposal for finding top-k PoI groups in response to a query. We show how problem parameter settings can be mapped to options that are meaningful to users. Further, although this kind of functionality is prone to combinatorial explo-sion, we will demonstrate that the functionality can be supported efficiently in practical settings. 1.