sis 20(28): e4

Research Article

Spatial Ambiguities Optimization in GIR

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  • @ARTICLE{10.4108/eai.13-7-2018.164556,
    author={Arun Kumar Yadav and Jay Kant Pratap Singh Yadav and Divakar Yadav},
    title={Spatial Ambiguities Optimization in GIR},
    journal={EAI Endorsed Transactions on Scalable Information Systems},
    volume={7},
    number={28},
    publisher={EAI},
    journal_a={SIS},
    year={2020},
    month={5},
    keywords={Geographical information retrieval, geoparsing, geotagging, gazetteer, spatial indexing, textual indexing},
    doi={10.4108/eai.13-7-2018.164556}
}
  • Arun Kumar Yadav
    Jay Kant Pratap Singh Yadav
    Divakar Yadav
    Year: 2020
    Spatial Ambiguities Optimization in GIR
    SIS
    EAI
    DOI: 10.4108/eai.13-7-2018.164556
Arun Kumar Yadav1, Jay Kant Pratap Singh Yadav2, Divakar Yadav1,*
  • 1: National Institute of Technology, Hamirpur (H.P.), India
  • 2: Ajay Kumar Garg Engineering College, Ghaziabad (U.P.), India
*Contact email: divakaryadav@nith.ac.in

Abstract

INTRODUCTION: Huge amount of geographically referenced information is available on World Wide Web and has become an excellent source for retrieval of desired information. Extraction of relevant information from such a huge unstructured source is not an easy task.

OBJECTIVES: In this paper, we propose a location based search engine, designing two indexes namely spatial index and inverted index. Using these indexes, we are able to solve toponym ambiguity and overlapping of documents.

METHODS: To handle toponym ambiguity problem, we designed and implemented architecture for directional web document search. The architecture poses spatial followed by textual indexing for toponym resolution and to reduce overlapping of documents in geographical locations.

RESULTS: The proposed architecture was implemented and tested on spatial and textural data sets.

CONCLUSION: The performance is measured in terms of precision and false positive parameters and found that the proposed architecture performs better for geo/geo and geo/non-geo search queries.

Keywords
Geographical information retrieval, geoparsing, geotagging, gazetteer, spatial indexing, textual indexing
Received
2020-04-16
Accepted
2020-05-07
Published
2020-05-14
Publisher
EAI
http://dx.doi.org/10.4108/eai.13-7-2018.164556

Copyright © 2020 Arun Kumar Yadav et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.