Abstract. This paper introduces GKB, a repository based on a domain independent meta-model for integrating geographic knowledge collected from multiple sources. We present the architecture, the repository design and the data cleaning and knowledge integration processes. We also describe the rules developed to add new knowledge to GKB. GKB includes tools for generating ontologies, which are being used by multiple semantic web applications. To illustrate how it is being used, we present some of the applications that interact with the repository or load ontologies created with GKB.

This paper describes our participation at the GeoCLEF 2005 task. We detail the main software components of our Geo-IR system, its adaptation for the participation at GeoCLEF and discuss the obtained results. The software architecture includes a geographic knowledge base, a text mining tool for geo-referencing documents, and a geo-ranking component to re-rank the results of a standard IR index according to geo-scopes. Evaluation shows that ranking with geographic scopes is heavily dependent on the information loaded in the knowledge base and on the ranking algorithm involved, requiring more than the correct assignment of a geo-scope to each document.

Extracting geographical information from various web sources is likely to be important for a variety of applications. One such use for this information is to enable the study of vernacular regions: informal places referred to on a day-to-day basis, but with no official entry in geographical resources, such as gazetteers. Past work in automatically extracting geographical information from the web to support the creation of vernacular regions has tended to focus on larger regions (e.g. “The British Midlands ” and “The South of France”). In this paper we report the results of preliminary work to investigate the success of using a simple geotagging approach and resources of varying granularity from the Ordnance Survey to extract geographical information from web pages. We find that the data gathered for smaller regions (compared with larger ones) is more “fine-grained ” which has an effect on the type of resource most useful for geo-tagging and its success.

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This article describes a geographical study on the usage of a search engine, focusing on the traffic details at the level of countries and continents. The main objective is to understand from a geographic point of view, how the needs of the users are satisfied, taking into account the geographic location of the host in which the search originates, and the host that contains the Web page that was selected by the user in the answers. Our results confirm that the Web is a cultural mirror of society and shed light on the implicit social network behind search. These results are also useful as input for the design of distributed search engines. 1.

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Abstract. Context-aware search in mobile web environments demands new retrieval methods that rank web resources based on the proximity to users ’ locations. This paper presents the indexing and ranking architecture of a new geographic web retrieval system that can accept the user location as input and ranks searched items based on the estimated distances between the users and the resources. We describe the criteria to be considered by a geographic similarity metric and the indexing data structures that we created for fast selection of web resouces based on proximity. 1

Abstract. This paper reports the participation of the University of Lisbon at the 2007 GeoCLEF task. We adopted a novel approach for GIR, focused on handling geographic features and feature types on both queries and documents, generating signatures with multiple geographic concepts as a scope of interest. We experimented new query expansion and text mining strategies, relevance feedback approaches and ranking metrics. 1

The NewsStand system is an example application of a general framework that we are developing to enable people to search for information using a map query interface, where the information results from monitoring the output of over 8,000 RSS news sources and is available for retrieval within minutes of publication. The advantage of doing so is that a map, coupled with an ability to vary the zoom level at which it is viewed, provides an inherent granularity to the search process that facilitates an approximate search. This distinguishes it from today’s prevalent keyword-based conventional search methods that provide a very limited facility for approximate searches which are realized primarily by permitting a match via use of a subset of the keywords. However, it is often the case that users do not have a firm grasp of which keyword to use, and thus would welcome the capability for the search to also take synonyms into account. In the case of queries to spatially-referenced data, the map query interface is a step in this direction as the act of pointing at a location (e.g., by the appropriate positioning of a pointing device) and making the interpretation of the precision of this positioning specification dependent on the zoom level is equivalent to permitting the use of spatial synonyms. The issues that arise in the design of such a system including the identification of words that correspond to geographic locations are discussed, and examples are provided of the utility of the approach, thereby representing a step forward in the emerging field of computational journalism.