Top-k spatial preference query ranks objects based on the score of feature objects in their spatial neighborhood. Top-k preference queries are crucial for wide range of location based services such as hotel browsing and apartment searching; several algorithms have been proposed to process them in Euclidean space. Although, few algorithms study top-k preference queries in a road network, however, they all focus on undirected road network. To the best of our knowledge, this is the first attempt to investigate the problem of processing the top-k spatial preference queries in a directed road networks. Computation of data object score requires examining the scores of feature objects in its spatial neighborhood. This may raise the processing cost resulting in high query processing time. Therefore, in this paper we propose a new preference query search algorithm called PSA that can efficiently answer the top-k spatial preference queries in directed road network. Experimental study shows that our algorithm significantly reduces the query processing time compared to baseline solution for a wide range of problem settings.

In this paper, we studied the problem of reverse k nearest neighbors (RkNN) in directed road network, where a road segment can have a particular orientation. A RNN query returns a set of data objects that take query point as their nearest neighbor. Although, much research has been done for RNN in Euclidean and undirected network space, very less attention has been paid to directed road network, where network distances are not symmetric. In this paper, we provided pruning rules which are used to minimize the network expansion while searching for the result of a RNN query. Based on these pruning rules we provide an algorithm named SWIFT for answering RNN queries in static directed road network. We evaluated SWIFT on a real world road network and our experimental results show that SWIFT significantly outperforms the naïve algorithm in terms of computational cost.Index Terms-reverse nearest neighbors, spatial query, directed road network.

There is strong epidemiological evidence, based on 15 prospective studies, 10 meta-analyses, and 5 systematic reviews involving more than 2.2 million patients, that alcohol consumption is a contributing factor for the development of breast cancer. The evidence regarding the effect of alcohol consumption on breast cancer outcome needs to be gathered in order to draw firm conclusions regarding alcohol consumption after breast cancer diagnosis. In this article, we aim to review the current literature regarding recurrence and all-cause and BC cause mortality and identify postulated. We would make suggestions for future research.

In this paper, we studied the problem of continuous reverse k nearest neighbors (RkNN) in directed road network, where a road segment can have a particular orientation. A RNN query returns a set of data objects that take query point as their nearest neighbor. Although, much research has been done for RNN in Euclidean and undirected network space, very less attention has been paid to directed road network, where network distances are not symmetric. In this paper, we provided pruning rules which are used to minimize the network expansion while searching for the result of a RNN query. Based on these pruning rules we provide an algorithm named SWIFT for answering RNN queries in continuous directed road network.