Geospatial data mining on the web: Discovering locations of emergency service facilities

WenWen Li, Michael Goodchild, Richard L. Church, Bin Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Identifying location-based information from the WWW, such as street addresses of emergency service facilities, has become increasingly popular. However, current Web-mining tools such as Google's crawler are designed to index webpages on the Internet instead of considering location information with a smaller granularity as an indexable object. This always leads to low recall of the search results. In order to retrieve the location-based information on the ever-expanding Internet with almost-unstructured Web data, there is a need of an effective Web-mining mechanism that is capable of extracting desired spatial data on the right webpages within the right scope. In this paper, we report our efforts towards automated location-information retrieval by developing a knowledge-based Web mining tool, CyberMiner, that adopts (1) a geospatial taxonomy to determine the starting URLs and domains for the spatial Web mining, (2) a rule-based forward and backward screening algorithm for efficient address extraction, and (3) inductive-learning-based semantic analysis to discover patterns of street addresses of interest. The retrieval of locations of all fire stations within Los Angeles County, California is used as a case study.

Original languageEnglish (US)
Title of host publicationAdvanced Data Mining and Applications - 8th International Conference, ADMA 2012, Proceedings
Pages552-563
Number of pages12
DOIs
StatePublished - Dec 1 2012
Event8th International Conference on Advanced Data Mining and Applications, ADMA 2012 - Nanjing, China
Duration: Dec 15 2012Dec 18 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7713 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Advanced Data Mining and Applications, ADMA 2012
CountryChina
CityNanjing
Period12/15/1212/18/12

Keywords

  • Emergency service facilities
  • Inductive learning
  • Information extraction
  • Information retrieval
  • Location-based services
  • Ontology
  • Web data mining

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Li, W., Goodchild, M., Church, R. L., & Zhou, B. (2012). Geospatial data mining on the web: Discovering locations of emergency service facilities. In Advanced Data Mining and Applications - 8th International Conference, ADMA 2012, Proceedings (pp. 552-563). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7713 LNAI). https://doi.org/10.1007/978-3-642-35527-1_46