[1]MENG Xiangfu,ZHANG Xiaoyan,ZHAO Lulu,et al.A location-text correlation-based top-k query and ranking approach for spatial objects[J].CAAI Transactions on Intelligent Systems,2020,15(2):235-242.[doi:10.11992/tis.201808011]
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A location-text correlation-based top-k query and ranking approach for spatial objects
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
15
Number of periods:
2020 2
Page number:
235-242
Column:
学术论文—自然语言处理与理解
Public date:
2020-03-05
- Title:
- A location-text correlation-based top-k query and ranking approach for spatial objects
- Keywords:
- spatial database; spatial keyword query; location-text correlation; probability density; representative object selection; top-k query and ranking
- CLC:
- TP311.1
- DOI:
- 10.11992/tis.201808011
- Abstract:
- Due to the large size of spatial databases, a common spatial keyword query often leads to the problem of too many answers. To deal with this problem, this paper proposes a location-text correlation-based top- k query and ranking approach for spatial objects, which aims to find the typical spatial objects with high text relevancy and location proximity. This approach consists of offline processing and online query steps. The offline step scores the relationship between any pair of spatial objects by considering their location proximity and text similarity. Then, by using a probabilistic density-based representative spatial object selection method, a set of representatives over the spatial objects is selected to build a corresponding spatial object sequence. In the online query period, when a user issues a spatial keyword query, the location-text correlation between the query and representative objects is evaluated, and then, the top- k typical relevant objects can be expeditiously picked using the threshold algorithm (TA) algorithm over the sequences corresponding to representative spatial objects. The experiments demonstrate that the proposed top- k query and ranking approach can closely meet users’ needs, with high precision, typicality, and good performance.
- References:
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