Probabilistic retrieval based on staged logistic regression
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic models in information retrieval
The Computer Journal - Special issue on information retrieval
Using statistical testing in the evaluation of retrieval experiments
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
ACM Transactions on Information Systems (TOIS)
Inferring probability of relevance using the method of logistic regression
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Topological relations in the world of minimum bounding rectangles: a study with R-trees
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Information Sciences: an International Journal
On Relevance, Probabilistic Indexing and Information Retrieval
Journal of the ACM (JACM)
Information Retrieval
Modern Information Retrieval
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
The unified probabilistic model for IR
SIGIR '82 Proceedings of the 5th annual ACM conference on Research and development in information retrieval
Proceedings of the Ninth International Conference on Data Engineering
Computing Geographical Scopes of Web Resources
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Geographical Information Retrieval with Ontologies of Place
COSIT 2001 Proceedings of the International Conference on Spatial Information Theory: Foundations of Geographic Information Science
GeoVSM: An Integrated Retrieval Model for Geographic Information
GIScience '02 Proceedings of the Second International Conference on Geographic Information Science
Detecting dominant locations from search queries
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Hybrid index structures for location-based web search
Proceedings of the 14th ACM international conference on Information and knowledge management
A confidence-based framework for disambiguating geographic terms
HLT-NAACL-GEOREF '03 Proceedings of the HLT-NAACL 2003 workshop on Analysis of geographic references - Volume 1
Geographic IR and visualization in time and space
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 2nd international workshop on Geographic information retrieval
Using the geographic scopes of web documents for contextual advertising
Proceedings of the 6th Workshop on Geographic Information Retrieval
Learning to rank for geographic information retrieval
Proceedings of the 6th Workshop on Geographic Information Retrieval
Geographic information retrieval and digital libraries
ECDL'09 Proceedings of the 13th European conference on Research and advanced technology for digital libraries
Relevance ranking in Geographical Information Retrieval
SIGSPATIAL Special
SIGSPATIAL Special
Relevance and ranking in geographic information retrieval
FDIA'11 Proceedings of the Fourth BCS-IRSG conference on Future Directions in Information Access
Hi-index | 0.00 |
This research compares the geographic information retrieval (GIR) performance of a set of logistic regression models with those of five non-probabilistic methods that compute a spatial similarity score for a query-document pair. All methods are applied to a test collection of queries and documents indexed spatially by two convex conservative geometric approximations: the minimum bounding box (MBB) and the convex hull. In the comparison, the tested logistic regression models outperform, in terms of standard information retrieval recall and precision measures, all of the non-probabilistic methods. The retrieval performance achieved by the logistic regression models on MBB approximations is similar to that achieved by the use of the non-probabilistic methods on convex hulls. Although these results are valid only for the test collection used in this study, they suggest that a logistic regression approach to GIR provides an alternative to the use of higher-quality geometric representations that are more difficult to obtain, implement, and process. Additionally, this research demonstrates the ability of a probabilistic approach to effectively incorporate information about geographic context in the spatial ranking process.