Motive-based search: Computing regions from large knowledge bases using geospatial coordinates

To create a better search experience for end users and to satisfy their actual intents even for vaguely formulated queries, a contemporary search engine has to go beyond simple keyword-based retrieval concepts. For a geospatial search, where user queries can be quite complex such as “places for winter sport holidays and culture in Central Europe”, we introduce the notion of geospatial motifs denoting traits of geographical regions. Defining a motif by a set of geospatial entities with certain characteristics, we present an approach to inferring important regions for the motif based on density of these entities. The evaluation of the approach for several motifs showed that the inferred regions are among the most popular places for a motif of interest according to the opinion of several experts and official rankings. Thus, we claim that the presented semi-automatic process of detecting regions for geospatial motifs can contribute to more powerful and flexible search applications which are able to answer user queries containing complex geospatial concepts.