The need for better Web search tools is getting increasing attention nowadays. About 20% of the queries currently submitted to search engines include geographic references. Thus, it is particularly important to work with the semantics of such queries, both by understanding the terminology and by recognizing geographic references in natural language text. In this paper, we explore the use of natural language expressions, which we call positioning expressions, to perform geographic searches on the Web, without resorting to geocoded data or gazetteers. Such positioning expressions denote the location of a subject of interest with respect to a landmark. Our approach leads to a query expansion technique that can be explored by virtually any keyword‐based search engine. Results obtained in our experiments show an expressive improvement over the traditional keyword‐based search and a potential path for tackling many kinds of common geographic queries.
An important activity in the design of a particular database application consists in identifying the integrity constraints that must hold on the database, and that are used to detect and evaluate inconsistencies. It is possible to improve data quality by imposing constraints upon data entered into the database. These constraints must be identified and recorded at the database design level. However, it is clear that modeling geographic data requires models which are more specific and capable of capturing the semantics of geographic data. Within a geographic context, topological relations and other spatial relationships are fundamentally important in the definition of spatial integrity rules. This paper discusses the relationship that exists between the nature of spatial information, spatial relationships, and spatial integrity constraints, and proposes the use of OMT-G, an extension of the OMT model for geographic applications, at an early stage in the specification of integrity constraints in spatial databases. OMT-G provides adequate primitives for representing spatial data, supports spatial relationships, and allows topological, semantic and user integrity rules to be specified in the database schema.
When users need to find something on the Web that is related to a place, chances are place names will be submitted along with some other keywords to a search engine. However, automatic recognition of geographic characteristics embedded in Web documents, which would allow for a better connection between documents and places, remains a difficult task. We propose an ontology-driven approach to facilitate the process of recognizing, extracting, and geocoding partial or complete references to places embedded in text. Our approach combines an extraction ontology with urban gazetteers and geocoding techniques. This ontology, called OnLocus, is used to guide the discovery of geospatial evidence from the contents of Web pages. We show that addresses and positioning expressions, along with fragments such as postal codes or telephone area codes, provide satisfactory support for local search applications, since they are able to determine approximations to the physical location of services and activities named within Web pages. Our experiments show the feasibility of performing automated address extraction and geocoding to identify locations associated to Web pages. Combining location identifiers with basic addresses improved the precision of extractions and reduced the number of false positive results. Geoinformatica (2011) 15:609-631
scite is a Brooklyn-based startup that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.