Abstract
As the availability and utilisation of online data blossoms, automated online searches—whether to answer a simple question, seek specific sensor readings, or investigate research in a particular domain—have raised a number of issues. Simple search tools do not access the deep web of services and online forms, and cannot handle knowledge domain-specific search problems, but specialist search tools can have a narrow domain and applicability. Some online tools circumvent these problems by putting more filter controls into the hands of users, but this leads to more complex interfaces which can raise usability barriers. A distributed approach, where specialised search agents act autonomously to find contextualised information, can provide a useful compromise between a simple, general search interface and specialist searches. This paper outlines work in progress on design and use of specialist search agents, with a case study to find public transportation bus stops within a spatial region. The approach is demonstrated with a proof of concept web interface, developed to interpret a text query to find and show bus stop locations within a named boundary by coordinating multiple online search agents. Search agents were designed to follow a common model to allow for future development of agent types, including specialist agents used in the case study to search standard open web services and extract spatial features.
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Huang, W., & Webster, D. (2004). Enabling context-aware agents to understand semantic resources on the WWW and the semantic web. In 2004 IEEE/WIC/ACM international conference on web intelligence (WI ‘04). IEEE Computer Society.
Zhao, T., Zhang, C., Wei, M., & Peng, Z.-R. (2008). Ontology-based geospatial data query and integration. In Cova, T. J., et al. (Eds.) Geographic information science: 5th international conference, GIScience 2008, Park City, UT, USA, September 23–26, 2008, Proceedings (pp. 370–392). Springer: Berlin, Heidelberg.
Yue, P., Di, L., Yang, W., Yu, G., & Zhao, P. (2007). Semantics-based automatic composition of geospatial Web service chains. Computers & Geosciences, 33(5), 649–665.
Zhao, P., Foerster, T., & Yue, P. (2012). The geoprocessing web. Computers & Geosciences, 47, 3–12.
Tian, Y., & Huang, M. (2012). Enhance discovery and retrieval of geospatial data using SOA and Semantic Web technologies. Expert Systems with Applications, 39(16), 12522–12535.
Viroli, M., Ricci, A., & Omicini, A. (2006). Operating instructions for intelligent agent coordination. Knowledge Engineering Review, 21(1), 49–69.
Gabrilovich, E., & Markovitch, S. (2009). Wikipedia-based semantic interpretation for natural language processing. Journal of Artificial Intelligence Research, 34, 443–498.
Cilibrasi, R. L., & Vitanyi, P. M. B. (2007). The google similarity distance. IEEE Transactions on Knowledge and Data Engineering, 19(3), 370–383.
Rybinski, M., & Aldana-montes, J. F. (2014). Calculating semantic relatedness for biomedical use in a knowledge-poor environment. BMC Bioinformatics, 15(Suppl 14), S2.
Dong, H., Hussain, F.K., & Chang, E. (2008). A survey in semantic search technologies. In Second IEEE international conference on digital ecosystems and technologies. Phitsanulok, Thailand: IEEE.
Bogdanović, M., Stanimirović, A., & Stoimenov, L. (2015). Methodology for geospatial data source discovery in ontology-driven geo-information integration architectures. Web Semantics: Science, Services and Agents on the World Wide Web, 32, 1–15.
Chun, S. A., & Warner, J. (2008). Semantic annotation and search for deep web services. In Tenth IEEE conference on E-commerce technology and the 5th IEEE conference on enterprise computing, E-commerce and E-services (pp. 389–395). IEEE: Washington, DC, USA.
Madhavan, J., Afanasiev, L., Antova, L. & Halevy, A. (2009). Harnessing the deep web: Present and future. ArXiv.
Zhang, C., Zhao, T., & Li, W. (2013). Towards improving query performance of web feature services (WFS) for disaster response. ISPRS International Journal of Geo-Information, 2(1), 67–81.
Moncrieff, S., West, G. A. W., Cosford, J., Mullan, N., & Jardine, A. (2014). An open source, server-side framework for analytical web mapping and its application to health. International Journal of Digital Earth, 7(4), 294–315.
Rautenbach, V., Coetzee, S., & Iwaniak, A. (2013). Orchestrating OGC web services to produce thematic maps in a spatial information infrastructure. Computers, Environment and Urban Systems, 37, 107–120.
Zhang, C., Zhao, T., Li, W., & Osleeb, J. P. (2010). Towards logic-based geospatial feature discovery and integration using web feature service and geospatial semantic web. International Journal of Geographical Information Science, 24(6), 903–923.
Bone, C., Ager, A., Bunzel, K., & Tierney, L. (2014). A geospatial search engine for discovering multiformat geospatial data across the Web. International Journal of Digital Earth, 9(1), 47–62.
Adams, B., & McKenzie, G. (2013). Inferring thematic places from spatially referenced natural language descriptions. In D. Z. Sui, S. Elwood, & M. F. Goodchild, (Eds.) Crowdsourcing geographic knowledge: Volunteered geographic information (VGI) in theory and practice (pp. 201–221). Springer: Dordrecht.
Acknowledgments
The research reported in this paper was supported by the Australian Primary Health Care Research Institute (APHCRI), which was supported by a grant from the Australian Government Department of Health. The information and opinions contained in it do not necessarily reflect the views or policy of the Australian Primary Health Care Research Institute or the Australian Government Department of Health. The Cooperative Research Centre for Spatial Information, whose activities were funded by the Australian Commonwealth Cooperative Research Centres Programme, has supported this work.
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This paper was revised from the paper initially presented in FOSS4G Seoul 2015 Conference.
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Gulland, EK., Moncrieff, S. & West, G. Distributed agents for online spatial searches. Spat. Inf. Res. 24, 191–202 (2016). https://doi.org/10.1007/s41324-016-0020-3
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DOI: https://doi.org/10.1007/s41324-016-0020-3