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
Mining significant semantic locations from GPS data
TL;DR: A general framework for the mining of semantically meaningful, significant locations, e.g., shopping malls and restaurants, from GPS data is proposed and is capable of outperforming baseline methods and an extension of an existing proposal.
Journal ArticleDOI
Spatial keyword query processing: an experimental evaluation
TL;DR: An all-around survey of 12 state-of-the-art geo-textual indices and proposes a benchmark that enables the comparison of the spatial keyword query performance, thus uncovering new insights that may guide index selection as well as further research.
Proceedings ArticleDOI
Collective spatial keyword querying
TL;DR: This paper defines the problem of retrieving a group of spatial web objects such that the group's keywords cover the query's keywords and such that objects are nearest to the query location and have the lowest inter-object distances and designs exact and approximate solutions with provable approximation bounds to the problems.
Book ChapterDOI
Efficient processing of top-k spatial keyword queries
TL;DR: A novel index to improve the performance of top-k spatial keyword queries named Spatial Inverted Index (S2I), which maps each distinct term to a set of objects containing the term and can be retrieved efficiently in decreasing order of keyword relevance and spatial proximity.
Journal ArticleDOI
Retrieving top-k prestige-based relevant spatial web objects
TL;DR: Empirical studies with real-world spatial data demonstrate that LkPT queries are more effective in retrieving web objects than a previous approach that does not consider the effects of nearby objects; and they show that the proposed algorithms are scalable and outperform a baseline approach significantly.
References
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Proceedings ArticleDOI
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Proceedings ArticleDOI
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Proceedings ArticleDOI
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Proceedings ArticleDOI
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