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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

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With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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  1/2012 - 8

Enabling Semantic Queries Against the Spatial Database

PENG, X. See more information about PENG, X. on SCOPUS See more information about PENG, X. on IEEExplore See more information about PENG, X. on Web of Science, HUANG, Z. See more information about HUANG, Z. on SCOPUS See more information about HUANG, Z. on SCOPUS See more information about HUANG, Z. on Web of Science
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Download PDF pdficon (690 KB) | Citation | Downloads: 830 | Views: 2,700

Author keywords
spatial database, semantic web, query processing

References keywords
No relevant keywords could be extracted from the references.

About this article
Date of Publication: 2012-02-28
Volume 12, Issue 1, Year 2012, On page(s): 45 - 50
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.01008
Web of Science Accession Number: 000301075000008
SCOPUS ID: 84860743212

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The spatial database based upon the object-relational database management system (ORDBMS) has the merits of a clear data model, good operability and high query efficiency. That is why it has been widely used in spatial data organization and management. However, it cannot express the semantic relationships among geospatial objects, making the query results difficult to meet the user's requirement well. Therefore, this paper represents an attempt to combine the Semantic Web technology with the spatial database so as to make up for the traditional database's disadvantages. In this way, on the one hand, users can take advantages of ORDBMS to store and manage spatial data; on the other hand, if the spatial database is released in the form of Semantic Web, the users could describe a query more concisely with the cognitive pattern which is similar to that of daily life. As a consequence, this methodology enables the benefits of both Semantic Web and the object-relational database (ORDB) available. The paper discusses systematically the semantic enriched spatial database's architecture, key technologies and implementation. Subsequently, we demonstrate the function of spatial semantic queries via a practical prototype system. The query results indicate that the method used in this study is feasible.

References | Cited By  «-- Click to see who has cited this paper

[1] S. Shekhar and S. Chawla, Spatial Databases: a Tour. Upper Saddle River, N.J. : Prentice Hall, 2003.

[2] D. H. Kim, K. H. Ryu and C. H. Park, "Design and implementation of spatiotemporal database query processing system," The Journal of Systems and Software, vol. 60, no. 1, pp. 37-49, January 2002.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 8]

[3] G. Langran, "A review of temporal database research and its use in GIS applications," International Journal of Geographical Information Systems, vol. 3, no.3, pp. 215-232, 1998.
[CrossRef] [SCOPUS Times Cited 87]

[4] M. J. Egenhofer, "SpatialSQL : a query and presentation language," IEEE Transactions on Knowledge and Data Engineering, vol. 6, no. 1, pp.86-95, 1994.
[CrossRef] [Web of Science Times Cited 149] [SCOPUS Times Cited 216]

[5] Z. Huang, Y. Fang, B. Chen, L. Wu and M. Pan. "Building the Distributed Geographic SQL Workflow in the Grid Environment," International Journal of Geographical Information Science, vol.25, no.7, pp.1117-1145, 2011.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 4]

[6] F. Baader, C. Lutz, M. Milicic, U. Sattler and F.Wolter, "A description logic based approach to reasoning about web services," in Proceedings of the WWW 2005 Workshop on Web Service Semantics (WSS2005), Chiba, Japan, 2005.

[7] G. Claudio, A.H. Carlos and V. Alejandro, "Introducing Time into RDF," IEEE Transactions on Knowledge and Data Engineering, vol. 19, no. 2, pp. 207-218, 2007.
[CrossRef] [Web of Science Times Cited 75] [SCOPUS Times Cited 151]

[8] T.W. Wang, B. Parsia and J. Hendler. "A Survey of the Web Ontology Landscape," in Proceedings of the 5th International Semantic Web Conference (ISWC2006), Athens,USA,2006.

[9] I. Horrocks, P. F. Patel-Schneider, and F. van-Harmelen. "From SHIQ and RDF to OWL: the making of a web ontology language," Journal of Web Semantics, vol. 1, no. 1, pp. 7-26, 2003.
[CrossRef] [SCOPUS Times Cited 980]

[10] S. A, Mcilraith, T. C. Son and H. Zeng, "Semantic web services," IEEE Intelligent Systems, vol. 16, no. 2, pp. 46-53, 2001.
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[11] W. A. Woods, "What's in a link: foundations for semantic networks," in D. Bobrow and A. Collins (eds.), Representation and Understanding: Studies in Cognitive Science. pp. 35-82, New York : Academic Press, 1975.

[12] P. Patel-Schneider and J. Simeon, "The yin/yang web: xml syntax and rdf semantics," in Proceedings of the 11th International World Wide Web Conference (WWW 2002), Honolulu,USA, 2002.

References Weight

Web of Science® Citations for all references: 1,030 TCR
SCOPUS® Citations for all references: 2,690 TCR

Web of Science® Average Citations per reference: 79 ACR
SCOPUS® Average Citations per reference: 207 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

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