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Route Recommendation based on Dynamic User Preference on Road Networks
http://doi.org/10.5626/JOK.2019.46.1.77
The current location based services provide maps and nearby information, or provide a route to a specific destination. A route recommendation system recommends the best route that suits the evaluation criteria for each user. The existing personalized path recommendation system recommends the route under the assumption that the user’s preference is constant regardless of the change of the time zone. However, there is a problem in that it does not reflect requirements that important factors to users can be different for each time zone, such as importance of moving distance in morning time and importance of risk in late time. In this paper, we propose a Dijkstra algorithm considering time attributes to overcome this limitation. In addition, we suggest an efficient algorithm that can search the path reflecting the change of the weight of the preference factor according to the time zone using the G-tree index structure that effectively expresses the road network.
A Predictive Query Processing Method Considering the Movement of both a User and Objects
http://doi.org/10.5626/JOK.2018.45.12.1302
Recently, with the increase in use of mobile devices such as smart phones and tablet PCs with GPS, it is possible to analyze a large volume of data aggregated from various sensors. Accordingly, a variety of location-based services (LBSs) have attracted attention. To effectively provide these services, techniques for efficient spatial query processing have been studied. In this paper, we propose a method to overcome the limitation of not returning the desired query result to the user, because existing studies did not consider movement of the user. Specifically, we propose an algorithm to efficiently process a predictive query in the road network that returns the best available K moving objects, in consideration of the time of the user`s moving and that of the user`s waiting. In this process, we apply the technique to gradually expand the range of user and object`s movement simultaneously. Also, an appropriate index structure is used to efficiently process queries even in the road network with a large number of vertices and moving objects. Experimental results reveal the difference in the query result compared to existing studies and also reveal significant results in terms of efficiency.
Privacy Budget Allocation Technique Based on Variable Length Window for Traffic Data Publishing with Differential Privacy in Road Networks
Gunhyung Jo, Kangsoo Jung, Seog Park
http://doi.org/10.5626/JOK.2018.45.9.957
Recently, traffic volume data at every timestamp have been required in many fields such as road design and traffic analysis. Such traffic volume data may contain individual sensitive location information, which leads to privacy violation such as personal route exposure. Differential privacy has the advantage of protecting sensitive personal information in this situation while controlling the data utility by inserting noise to raw data. However, because of the traffic volume data generally would be an infinite size over time, there is a drawback in that data is useless because insufficiently large scaled noise is inserted. In order to overcome this drawback, researches have been conducted on applying the differential privacy technique only to the traffic volume data contained in windows of a certain time range. However, in the previous studies, the length of the window was fixed, inducing a limit whereby the correlation of the road sections and the time-specificity are not considered. In this paper, we propose a variable length window technique considering the correlation between road segments and time-specificity.
An Efficient Algorithm for Monitoring Continuous Top-k Queries
JaeHee Jang, HaRim Jung, YougHee Kim, Ung-Mo Kim
In this study, we propose an efficient method for monitoring continuous top-k queries. In contrast to the conventional top-k queries, the presented top-k query considers both spatial and non-spatial attributes. We proposed a novel main-memory based grid access method, called Bit-Vector Grid Index (BVGI). The proposed method quickly identifies whether the moving objects are included in some of the grid cell by encoding a non-spatial attribute value of the moving object to bit-vector. Experimental simulations demonstrate that the proposed method is several times faster than the previous method and uses considerably less memory.
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