The importance of query processing over uncertain information has recently arisen thanks to its wide usage in many real-world applications. Within the context of uncertain databases, previous work have studied several query types like nearest neighbor query, vary question, top-$k$ question, skyline query, and similarity be part of. In this paper, we have a tendency to specialize in another necessary query, particularly probabilistic group nearest neighbor query (PGNN), within the uncertain database, which conjointly has several applications. Specifically, given a set, Q, of question points, a PGNN question retrieves data objects that minimize the aggregate distance (e.g. total, min, and max) to question set Q. Thanks to the inherent uncertainty of data objects, previous techniques to answer group nearest neighbor question (GNN) can't be directly applied to our PGNN problem. Motivated by this, we tend to propose effective pruning strategies, specifically spatial pruning and probabilistic pruning, to scale back the PGNN search space, which will be seamlessly integrated into our PGNN question procedure. Extensive experiments have demonstrated the efficiency and effectiveness of our proposed approach, in terms of the wall clock time and the speed-up ratio against linear scan.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE :Accurate Location Tracking From CSI-Based Passive Device-Free Probabilistic Fingerprinting - 2018ABSTRACT:The research on indoor localization has received great interest in recent times. This has been fueled by
PROJECT TITLE :A Probabilistic Framework for Structural Analysis and Community Detection in Directed Networks - 2018ABSTRACT:There's growing interest in structural analysis of directed networks. Two major points that require
PROJECT TITLE :Probabilistic Optimization of Resource Distribution and Encryption for Data Storage in the Cloud - 2018ABSTRACT:During this Project, we tend to develop a decentralized probabilistic technique for performance optimization
PROJECT TITLE :Road Traffic Speed Prediction: A Probabilistic Model Fusing Multi-Source Data - 2018ABSTRACT:Road traffic speed prediction could be a difficult downside in intelligent transportation system (ITS) and has gained
PROJECT TITLE :Probabilistic Error Modeling for Approximate Adders - 2017ABSTRACT:Approximate adders are widely being advocated as a means to attain performance gain in error resilient applications. In this paper, a generic methodology

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry