Supporting Quality-Based Image Retrieval Through User Preference Learning

Giorgos Mountrakis, Anthony Stefanidis, Isolde Schlaisich, Peggy Agouris
2004 Photogrammetric Engineering and Remote Sensing  
It is common for modern geospatial libraries to contain multiple datasets that cover the same area but differ only in some specific quality attributes (e.g., resolution and precision). This is affecting the concept of content-based geospatial queries, as simple coverage-based query mechanisms (e.g., declaring a specific area of interest) as well as theme-based query mechanisms (e.g., requesting a black and white aerial photo or multispectral satellite imagery) are rendered inadequate to
more » ... and access specific datasets in such collections. In this paper we introduce a novel approach to handle data quality attributes in geospatial queries. Our approach is characterized by the ability to model and learn user preferences, thus establishing user profiles that allow us to customize image queries for improving their functionality in a constantly diversifying geospatial user community.
doi:10.14358/pers.70.8.973 fatcat:m6gqo7a6xrbgpoer7dpqlpra2e