Challenges to evaluation of multilingual geographic information retrieval in GeoCLEF

This is the third year of the evaluation of geographic information retrieval (GeoCLEF) within the Cross-Language Evaluation Forum (CLEF). GeoCLEF 2006 presented topics and documents in four languages (English, German, Portuguese and Spanish). After two years of evaluation we are beginning to understand the challenges to both Geographic Information Retrieval from text and of evaluation of the results of geographic information retrieval. This poster enumerates some of these challenges to evaluation and comments on the limitations encountered in the first two evaluations

A geo-temporal information extraction service for processing descriptive metadata in digital libraries

In the context of digital map libraries, resources are usually described according to metadata records that define the relevant subject, location, time-span, format and keywords. On what concerns locations and time-spans, metadata records are often incomplete or they provide information in a way that is not machine-understandable (e.g. textual descriptions). This paper presents techniques for extracting geotemporal information from text, using relatively simple text mining methods that leverage on a Web gazetteer service. The idea is to go from human-made geotemporal referencing (i.e. using place and period names in textual expressions) into geo-spatial coordinates and time-spans. A prototype system, implementing the proposed methods, is described in detail. Experimental results demonstrate the efficiency and accuracy of the proposed approaches

Retrieval of similar travel routes using GPS tracklog place names

GPS tracklogs provide a valuable record of routes travelled. In this paper we describe initial experiments exploring the use of text information retrieval techniques for the location of similar trips from within a GPS tracklog. We performed the experiment on a dataset of 528 individual trips gathered over a seven month time period from a single user. The results of our preliminary study suggest that traditional text-based information retrieval techniques can indeed be used to locate similar and related tracklogs

Linking archival data to location A case study at the UK National Archives

Purpose The National Archives (TNA) is the UK Government's official archive. It stores and maintains records spanning over a 1,000 years in both physical and digital form. Much of the information held by TNA includes references to place and frequently user queries to TNA's online catalogue involve searches for location. The purpose of this paper is to illustrate how TNA have extracted the geographic references in their historic data to improve access to the archives. Design/methodology/approach To be able to quickly enhance the existing archival data with geographic information, existing technologies from Natural Language Processing (NLP) and Geographical Information Retrieval (GIR) have been utilised and adapted to historical archives. Findings Enhancing the archival records with geographic information has enabled TNA to quickly develop a number of case studies highlighting how geographic information can improve access to large‐scale archival collections. The use of existing methods from the GIR domain and technologies, such as OpenLayers, enabled one to quickly implement this process in a way that is easily transferable to other institutions. Practical implications The methods and technologies described in this paper can be adapted, by other archives, to similarly enhance access to their historic data. Also the data‐sharing methods described can be used to enable the integration of knowledge held at different archival institutions. Originality/value Place is one of the core dimensions for TNA's archival data. Many of the records which are held make reference to place data (wills, legislation, court cases), and approximately one fifth of users' searches involve place names. However, there are still a number of open questions regarding the adaptation of existing GIR methods to the history domain. This paper presents an overview over available GIR methods and the challenges in applying them to historical data