Abstract

This paper proposes a method of ranking geographic entities (places) where a purpose, given as a query, can be achieved. Most existing map search engines accept only the name of a place or the type of a place. Thus when searchers want to find a suitable place for ``guitar practice'', they have to input a place type such as ``music studio''. To create such a query, prior knowledge (\textit{i.e.}, that a music studio is suitable for playing guitar) is required. Our proposed method uses online review information on places to enable direct place retrieval from a given purpose query. Our method creates a bipartite graph consisting of places and the words that appear in the reviews of these places. The relevance between the given keyword query and a place is calculated by using the Random Walk with Restart algorithm. Additionally, we expand the graph with three hypotheses: 1) places that are suitable for the same purpose are similar to each other, and purposes that can be achieved in the same place are similar to each other, 2) the same purpose can be achieved in places with similar metadata, and 3) purposes which have semantically similar meaning can be achieved in the same places. Through an experiment using real review data taken from Google Maps, the usefulness of the proposed method was demonstrated. In particular, experimental result shows that the expansion by places' metadata is effective for finding more relevant places.

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