Tehnički vjesnik, Vol. 31 No. 2, 2024.
Izvorni znanstveni članak
https://doi.org/10.17559/TV-20230511000622
FBF: A High-Efficient Query Mechanism for Keyword Search in Online Social Networks
Jinzhou Huang
; School of Computer Engineering, Hubei University of Arts and Science, No. 296, Longzhong Road, Xiangyang, 441053, China
Yan Tong
; College of Science, Huazhong Agricultural University, No. 1 Shizishan Street, Hongshan Distr, Wuhan, 430070, China
Bo Hang
; School of Computer Engineering, Hubei University of Arts and Science, No. 296, Longzhong Road, Xiangyang, 441053, China
Degang Xu
; School of Computer Engineering, Hubei University of Arts and Science, No. 296, Longzhong Road, Xiangyang, 441053, China
Feng Wang
; School of Computer Engineering, Hubei University of Arts and Science, No. 296, Longzhong Road, Xiangyang, 441053, China
Jing Yu
; School of Computer and Big Data Science, Jiujiang University, No. 551, Qianjin East Road, Jiujiang, Jiangxi 332005, China
Sažetak
The widespread adoption of online social networks has facilitated content sharing among users. However, privacy controls restrict users' access to only a limited portion of the network, typically limited to direct connections or two-hop friends. Browsing relevant profiles and home pages has become a common practice for users, but the vast amount of data involved often hampers their ability to efficiently retrieve the desired information. This paper presents an efficient keyword search model designed to aid users in accessing the required information effectively. Leveraging advancements in Bloom filter technology, we propose a novel summary index called Friend-based Bloom filter (FBF), which enables large-scale full-text retrieval while reducing inter-server communication costs and query latency. We conduct a comprehensive simulation to evaluate our ranking model, and the results demonstrate the effectiveness of the FBF scheme. Specifically, our approach achieves a reduction of 92.4% in inter-server communication costs and 78.7% in query latency, with a high-search precision condition resulting in a remarkable 98.3% improvement.
Ključne riječi
friend-based Bloom filter; keyword search; online social network
Hrčak ID:
314823
URI
Datum izdavanja:
29.2.2024.
Posjeta: 149 *