Multi-Dimensional Scattered Ranking Methods for Geographic Information Retrieval*
نویسندگان
چکیده
منابع مشابه
Multi-Dimensional Scattered Ranking Methods for Geographic Information Retrieval
Geographic Information Retrieval is concerned with retrieving documents in response to a spatially related query. This paper addresses the ranking of documents by both textual and spatial relevance. To this end, we introduce multi-dimensional scattered ranking, where textually and spatially similar documents are ranked spread in the list, instead of consecutively. The effect of this is that doc...
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Geographic Information Retrieval is concerned with retrieving documents in response to a spatially related query. This paper addresses the ranking of documents by both textual and spatial relevance. To this end, we introduce distributed ranking, where similar documents are ranked spread in the list instead of consecutively. The effect of this is that documents close together in the ranked list ...
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Geographic Information Retrieval (GIR) is a specialized branch of traditional Information Retrieval (IR), which deals with the information related to geographic locations. One of the main challenges of GIR is to quantify the spatial relevance of documents and generate a pertinent ranking of the results according to the spatial information needs of user. Most of the current methods judge the rel...
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Recent evaluation results from Geographic Information Retrieval (GIR) indicate that current information retrieval methods are effective to retrieve relevant documents for geographic queries, but they have severe difficulties to generate a pertinent ranking of them. Motivated by these results in this paper we propose a novel method to re-order the list of documents returned by a GIR system. The ...
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Geographic Information Retrieval (GIR) has emerged as a new and promising tool for representation, storage, organisation of and access to geographic information. One of the current issues in GIR research is ranking of retrieved documents by both textual and geographic similarity measures. This paper describes an approach that learns GIR ranking functions using Genetic Programming (GP) methods b...
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ژورنال
عنوان ژورنال: GeoInformatica
سال: 2005
ISSN: 1384-6175,1573-7624
DOI: 10.1007/s10707-004-5622-6