A location based text mining method using ANN for geospatial KDD process

Authors:
Chung-Hong Lee;Hsin-Chang Yang;Shih-Hao Wang
Affiliations:
Dept of Electrical Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan;Dept of Information Management, National Kaohsiung University, Kaohsiung, Taiwan;Dept of Electrical Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan
Venue:
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
Year:
2010

Citing 12
Cited 1

A training algorithm for optimal margin classifiers

COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Support-Vector Networks

Machine Learning
Geospatial mapping and navigation of the web

Proceedings of the 10th international conference on World Wide Web
Geographical Information Retrieval with Ontologies of Place

COSIT 2001 Proceedings of the International Conference on Spatial Information Theory: Foundations of Geographic Information Science
Mining frequent geographic patterns with knowledge constraints

GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
A Hybrid Classification Scheme for Mining Multisource Geospatial Data

ICDMW '07 Proceedings of the Seventh IEEE International Conference on Data Mining Workshops
Using Geographic Signatures as Query and Document Scopes in Geographic IR

Advances in Multilingual and Multimodal Information Retrieval
Geographic features in web search retrieval

Proceedings of the 2nd international workshop on Geographic information retrieval
Density based co-location pattern discovery

Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
A sweep-line algorithm for spatial clustering

Advances in Engineering Software
Data mining of maps and their automatic region-time-theme classification

SIGSPATIAL Special
Support vector machine techniques for nonlinear equalization

IEEE Transactions on Signal Processing

An information fusion approach to integrate image annotation and text mining methods for geographic knowledge discovery

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

With the increasing needs of location information, applications of geospatial information have gained a lot of attention in both research and commercial organizations Extraction of geospatial knowledge from the information content has been thus becoming a important process Among theses applications, a typical example is to discover relationships between various geospatial texts/data and specific locations In this paper, we describe a location based text mining approach using Artificial Neural Networks (ANN) to classify texts into various categories based on their geospatial features, with the aims to discovering relationships between documents and zones First, the collected documents were mapped to corresponding zones by the Adaptive Affinity Propagation (Adaptive AP) clustering techniques, then we performed framed maximize zones by means of Fuzzy ARTMAP (FAM) and Support Vector Machines (SVM) methods, allowing the results of relationships between documents and zones to be well presented Eventually, we compared our experimental results with that of baseline models using Self-organizing maps (SOM) and Learning Vector Quantization (LVQ) methods The preliminary results show that our platform framework has potential for geospatial knowledge discovery.