Journal ArticleDOI
Efficient retrieval of the top-k most relevant spatial web objects
Gao Cong,Christian S. Jensen,Dingming Wu +2 more
- Vol. 2, Iss: 1, pp 337-348
TLDR
A new indexing framework for location-aware top-k text retrieval that encompasses algorithms that utilize the proposed indexes for computing the top- k query, thus taking into account both text relevancy and location proximity to prune the search space.Abstract:
The conventional Internet is acquiring a geo-spatial dimension. Web documents are being geo-tagged, and geo-referenced objects such as points of interest are being associated with descriptive text documents. The resulting fusion of geo-location and documents enables a new kind of top-k query that takes into account both location proximity and text relevancy. To our knowledge, only naive techniques exist that are capable of computing a general web information retrieval query while also taking location into account.This paper proposes a new indexing framework for location-aware top-k text retrieval. The framework leverages the inverted file for text retrieval and the R-tree for spatial proximity querying. Several indexing approaches are explored within the framework. The framework encompasses algorithms that utilize the proposed indexes for computing the top-k query, thus taking into account both text relevancy and location proximity to prune the search space. Results of empirical studies with an implementation of the framework demonstrate that the paper's proposal offers scalability and is capable of excellent performance.read more
Citations
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Journal ArticleDOI
Diameter-Aware Extreme Group Queries
TL;DR: The diameter-aware extreme group query (DiaEG query) is proposed, which searches for good good groups such that their total satisfaction is not smaller than a given threshold and the best-satisfaction query searches for the best group that has the highest satisfaction.
Book ChapterDOI
Group Top- k Spatial Keyword Query Processing in Road Networks
TL;DR: This paper proposes a basic group query-processing algorithm by using three distinct index structures and proposes another more efficient algorithm based on the concept of Minimum Bounding Rectangle (MBR), which can significantly reduce the objects to be examined and thus achieve higher performance.
Book ChapterDOI
AXE: Objects Search in Mobile Volunteered Service
Yao Wu,Yao Wu,Wenjuan Liang,Wenjuan Liang,Yuncheng Wu,Yuncheng Wu,Hong Chen,Hong Chen,Cuiping Li,Cuiping Li +9 more
TL;DR: A new hybrid index is proposed for mobile spatial textual objects, called BIG-tree, and an improved threshold algorithm is proposed to efficiently process the top-k query based on the index.
Posted Content
Topic-based Community Search over Spatial-Social Networks (Technical Report)
Ahmed Al-Baghdadi,Xiang Lian +1 more
TL;DR: Wang et al. as mentioned in this paper proposed a novel problem, named community search over spatial-social networks (TCS-SSN), which retrieves community with high social influence, small traveling time, and covering certain keywords.
Journal ArticleDOI
An Efficient Top- $K$ Spatial Keyword Typicality and Semantic Query
TL;DR: A location-semantic relationship measuring method can capture the location similarity and semantic relevancy between spatial objects accurately and the efficiency of typicality analysis and TA-based top-k selection algorithm is demonstrated.
References
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Book
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TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
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Proceedings ArticleDOI
R-trees: a dynamic index structure for spatial searching
TL;DR: A dynamic index structure called an R-tree is described which meets this need, and algorithms for searching and updating it are given and it is concluded that it is useful for current database systems in spatial applications.
Proceedings ArticleDOI
The R*-tree: an efficient and robust access method for points and rectangles
TL;DR: The R*-tree is designed which incorporates a combined optimization of area, margin and overlap of each enclosing rectangle in the directory which clearly outperforms the existing R-tree variants.