A novel multi-objective SKG-skyline algorithm integrating spatial keyword data transformation
The spatial keyword skyline query effectively addresses user preferences, particularly for location-based service applications. However, existing approaches primarily focus on single-object queries and remain unsuitable for group-based computations. To fulfill the requirements for group-oriented queries, a novel spatial keyword group-based skyline query was proposed. Firstly, the spatial-keyword coefficient was introduced to transforms spatial coordinates and keyword semantics into numerical values. Then, a spatial-keyword grid index was designed to efficiently locate query positions and perform keyword-based object filtering. Building upon this foundation, pruning theorems and group classification principles were proved, followed by the development of a spatial keyword group-based skyline (SKG-skyline) algorithm. Experimental evaluations on real-world datasets demonstrate that our algorithm outperforms existing methods in computational efficiency.
Authors
- Quan Yu (ORCID: https://orcid.org/0000-0002-1757-9229)
- Xiaowei Cui (ORCID: https://orcid.org/0000-0003-0545-7408)
- Yixuan Chai
- Guohao Sun (ORCID: https://orcid.org/0000-0002-0310-0598)
- Leigang Dong
- Yuanjun Huang
Institutions
- Shanghai Lixin University of Accounting and Finance (CN)
- Donghua University (CN)
- BaiCheng Normal University (CN)
- Network Group (Czechia) (CZ)
- Alibaba Group (China) (CN)
Publication Details
- Journal
- Complex & Intelligent Systems
- Published
- 2026-03-23
- DOI
- https://doi.org/10.1007/s40747-026-02282-8
- Primary Topic
- Data Management and Algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00