Ilmenau, Techn. Universiẗat, Diss., 2003.

Magdeburg, University, Diss., 2004.

Diss. Nr. 8446 techn. Wiss. ETH Zürich. / Literaturverz. S. 133-140.

Geographic Information Retrieval (GIR) systems provide users with functionalities of representation, storage, organisation of and access to various types of electronic information resources based on their textual and geographic context. This thesis explores various aspects of the development, evaluation and application of GIR systems. The first study focuses upon the extraction and grounding of geographic information entities. My approach for this study consists of a hierarchical structure-based geographic relationship model that is used to describe connections between geographic information entities, and a supervised machine learning algorithm that is used to resolve ambiguities. The proposed approach has been evaluated on a toponym disambiguation task using a large collection of news articles. The second study details the development and validation of a GIR ranking mechanism. The proposed approach takes advantage of the power of the Genetic Programming (GP) paradigm with the aim of finding an optimal functional form that integrates both textual and geographic similarities between retrieved documents and a given user query. My approach has been validated by applying it to a large collection of geographic metadata documents. The third study addresses the problem of modelling the GIR retrieval process that takes into account both thematic and geographic criteria. Based on the Spreading Activation Network (SAN), the proposed model consists a two-layer associative network that is used to construct a structured search space; a constrained spreading activation algorithm that is used to retrieve and to rank relevant documents; and a geographic knowledge base that is used to provide necessary domain knowledge for network. The retrieval performance of my model has been evaluated using the GeoCLEF 2006 tasks. The fourth study discusses the publishing, browsing and navigation of geographic information on the World Wide Web. Key challenges in designing and implementing of a GIR user interface through which online content can be systematically organised based on their geospatial characteristics, and can be efficiently accessed and interrelated, are addressed. The effectiveness and the usefulness of the system are shown by applying it to a large collection of geo-tagged web pages.

Geographic Information Retrieval (GIR) systems provide users with functionalities of representation, storage, organisation of and access to various types of electronic information resources based on their textual and geographic context. This thesis explores various aspects of the development, evaluation and application of GIR systems. The first study focuses upon the extraction and grounding of geographic information entities. My approach for this study consists of a hierarchical structure-based geographic relationship model that is used to describe connections between geographic information entities, and a supervised machine learning algorithm that is used to resolve ambiguities. The proposed approach has been evaluated on a toponym disambiguation task using a large collection of news articles. The second study details the development and validation of a GIR ranking mechanism. The proposed approach takes advantage of the power of the Genetic Programming (GP) paradigm with the aim of finding an optimal functional form that integrates both textual and geographic similarities between retrieved documents and a given user query. My approach has been validated by applying it to a large collection of geographic metadata documents. The third study addresses the problem of modelling the GIR retrieval process that takes into account both thematic and geographic criteria. Based on the Spreading Activation Network (SAN), the proposed model consists a two-layer associative network that is used to construct a structured search space; a constrained spreading activation algorithm that is used to retrieve and to rank relevant documents; and a geographic knowledge base that is used to provide necessary domain knowledge for network. The retrieval performance of my model has been evaluated using the GeoCLEF 2006 tasks. The fourth study discusses the publishing, browsing and navigation of geographic information on the World Wide Web. Key challenges in designing and implementing of a GIR user interface through which online content can be systematically organised based on their geospatial characteristics, and can be efficiently accessed and interrelated, are addressed. The effectiveness and the usefulness of the system are shown by applying it to a large collection of geo-tagged web pages.

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