ETGP: Top-K Geography-Text P/S Approach without Threshold

Abstract

Social media are more and more popular. Subsequently, geography-text data has caused wide attention. Different from the traditional publish/subscribe (P/S), geography-text data is published and subscribed in the form of dynamic data flow in the mobile network. The difference raises higher demands for facility. However, previous top-k geography-text P/S approaches want to set a set of thresholds. A user should take time to set a threshold for each subscription, which is not facile enough. The threshold yields many weaknesses to users. Therefore, we herein propose an efficient top-k geography-text P/S approach that excludes the threshold, called ETGP. Our approach does not need users to set any threshold. Subsequently, the ETGP returns the highest score results to the subscriber without setting a threshold. Therefore, our approach can lessen redundant computations, promote the query integrity rate, and make P/S system easier for the user to use. Comprehensive experiments prove the efficiency of the proposed approach with high facility.

An Efficient Top-k Query Scheme Based on Multilayer Grouping

“…Top-k query [1] returns the best k results to the user from a large amount of data [2].Top-k query has a wide range of applications [3], such as e-commerce [4], car networking [5] and other fields. Recently, Google, Twitter, Facebook also need to use Top-k query to collect the top data.…”