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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Proceedings ArticleDOI
Partitioning strategies for spatio-textual similarity join
TL;DR: An alternate algorithm known as PPJ is explored, which suggests that load balancing is a fundamental issue affecting parallel implementations of STJoin algorithms, and a multi-threaded implementation of the global index approach is able to achieve far better speedup.
Journal ArticleDOI
Investigating TSP Heuristics for Location-Based Services
Weihuang Huang,Jeffrey Xu Yu +1 more
TL;DR: It is shown that it is possible to get high-quality TSP by precomputing/indexing, even though it is hard to prove by theorem, and several heuristics are identified by extensive performance studies over real datasets, TSPLIB benchmarks, the existing synthetic datasets and new synthetic datasets.
Journal ArticleDOI
Clue-based spatio-textual query
TL;DR: This work has deliberately designed data-quality-tolerant spatio-textual context similarity metric to cope with various data quality problems in both the clue and the POI database and developed an index called roll-out-star R-tree to dramatically improve the query processing efficiency.
Book ChapterDOI
Pay-as-you-go Approximate Join Top-k Processing for the Web of Data
TL;DR: This paper proposes the first approximate top-k join framework for Web data and queries in a pay-as-you-go manner and results are very promising: it could achieve up to 65% time savings, while maintaining a high precision/recall.
Journal ArticleDOI
iAggregator: Multidimensional relevance aggregation based on a fuzzy operator
TL;DR: A new fuzzy‐based operator, called iAggregator, for multidimensional relevance aggregation, which lies in its generalization of many classical aggregation functions and outperforms state‐of‐the‐art aggregation operators such as the Scoring and the And prioritized operators as well as some representative learning‐to‐rank algorithms.
References
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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
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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.