TY  - JOUR
ID  - SisLab2959
UR  - https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2959/
A1  - Du, Phuong Hanh
A1  - Pham, Hai Dang
A1  - Nguyen, Ngoc Hoa
Y1  - 2018/04//
N2  - This paper presents our approach to optimize the performance of both reading and writing concurrent operations on large-scale social network. Here, we focus on the directed, unweighted relationships among members in a social network. It can then be illustrated as a directed, unweighted graph. And determining the relationship between any two members is similar to finding the shortest path between two vertices. With such a large-scale dynamic social network, we face the problem of having concurrent operations from adding or removing edges dynamically while one may ask to determine the relationship between two members. To solve this issue, we propose an efficient parallel method based on (i) utilizing an appropriate data structure, (ii) parallelizing the updating actions and (iii) improving the performance of query processing by both reducing the searching space and computing in multi-threaded parallel. Our method was validated by the datasets from SigMod Contest 2016 and SNAP DataSet Collections with good experimental results compared to other solutions
PB  - Springer
JF  - Transactions on Computational Collective Intelligence
VL  - 29
SN  - 2190-9288
TI  - An Efficient Parallel Method for Optimizing Concurrent Operations on Social Networks
SP  - 182
AV  - none
EP  - 199
ER  -