Semantic enrichment of places. Understanding the meaning of public places from natural language texts

Abstract

In this thesis, we present our approach to the challenge of assigning semantic annotations to places, what we call Semantic Enrichment of Places. These annotations are automatically extracted by applying natural language processing and information extraction techniques that have been thoroughly applied and tested using the World Wide Web as the primary source. Here, we are particularly focused on extracting information that allows an external system to distinguish one place from other places that are spatially or conceptually close. This is because the meaning of a place is a function of its most salient features, present in the textual descriptions found in online resources about that place. In the situation under investigation, places correspond to Points Of Interest (POIs), as these are abundant on the Web. By de nition, a POI is a place with meaning to someone and, if it is available online, it is likely that that person's interest is shared by many people. In this approach, the Web is rst crawled to obtain a large number of POIs and then each of them is analyzed in order to obtain their individual Semantic Index : the set of words that best de ne them. Besides analyzing POIs, we also propose the application of such an approach in several different contexts and we integrate these contexts in a multi-faceted view of place.