Normally Top-k queries are widely used for retrieving a ranked set of ‘k’ most objects based on the individual user preferences. As an example in online market places customer typically search a ranked set of products that satisfy their needs. From the perspective of a manufacturer, it is imperative that her products appear in the highest ranked positions for many different user preferences. Ot...

In this paper, we apply an efficient top-k shortest distance routing algorithm to the link prediction problem and test its efficacy. We compare the results with other base line and state-of-the-art methods as well as with the shortest path. Our results show that using top-k distances as a similarity measure outperforms classical similarity measures such as Jaccard and Adamic/Adar.

The problem of popular routes is very interesting and important. The authors consider the top-k routes which sequentially pass through the referenced locations within the specified time span and proposed the RICK algorithm consisting of routable graph construction and route inference which successfully solved the top-k routes problem. The authors also conducted extensive experiments on real wor...

The general problem of answering top-k queries can be modeled using lists of data items sorted by their local scores. The most efficient algorithm proposed so far for answering top-k queries over sorted lists is the Threshold Algorithm (TA). However, TA may still incur a lot of useless accesses to the lists. In this paper, we propose two new algorithms which stop much sooner. First, we propose ...

The general problem of answering top-k queries can be modeled using lists of data items sorted by their local scores. The main algorithm proposed so far for answering top-k queries over sorted lists is the Threshold Algorithm (TA). However, TA may still incur a lot of useless accesses to the lists. In this paper, we propose two algorithms that are much more efficient than TA. First, we propose ...

Abstract We introduce the R everse S patial Top-k K eyword (RSK) query, which is defined as: given a query term q, an integer k and neighborhood size find all neighborhoods of that where q in top-k most frequent terms among social posts those . An obvious approach would be to partition dataset with uniform grid structure cell identify cells this keywords. However, answer incomplete since it onl...