DESIGN WEBSITE PORTAL INFORMATION CRIME-PRONE LOCATION USING THE CONCEPT OF CROWDSOURCING
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Y. H. Park, “Relationship Analysis between Crime Types and Social Attributes in South Korea,” Database Res., vol. 29, no. 2, pp. 81–94, 2013.
J. Bao, Y. Zheng, and M. F. Mokbel, “Location-based and preference-aware recommendation using sparse geo-social networking data,” in Proceedings of the 20th international conference on advances in geographic information systems, 2012, pp. 199–208.
S. Scellato and C. Mascolo, “Measuring user activity on an online location-based social network,” in 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2011, pp. 918–923.
G. Zichermann and C. Cunningham, Gamification by design: Implementing game mechanics in web and mobile apps. “ O’Reilly Media, Inc.,” 2011.
J. D. E. Sandig, R. M. Somoba, M. B. Concepcion, and B. D. Gerardo, “Mining online gis for crime rate and models based on frequent pattern analysis,” in Proceedings of the World Congress on Engineering and Computer Science, 2013, vol. 2, pp. 23–27.
G. K. Habibullayevich, X. Chen, and H. Shin, “Efficient filtering and clustering mechanism for google maps,” J. Adv. Manag. Sci., vol. 1, no. 1, pp. 107–111, 2013.
A. Nasridinov, S.-Y. Ihm, and Y.-H. Park, “A decision tree-based classification model for crime prediction,” in Information Technology Convergence, Springer, 2013, pp. 531–538.
J. J. Levandoski, M. Sarwat, A. Eldawy, and M. F. Mokbel, “Lars: A location-aware recommender system,” in 2012 IEEE 28th international conference on data engineering, 2012, pp. 450–461.
W. Ahmad, A. Zia, and U. Khalid, “A Google Map based social network (GMBSN) for exploring information about a specific territory,” 2013.
DOI: https://doi.org/10.26905/jeemecs.v3i1.3619
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