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  4. Coverage and diversity aware Top-k query for spatio-temporal posts
 
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2016
Conference Paper
Titel

Coverage and diversity aware Top-k query for spatio-temporal posts

Abstract
Large amounts of user-generated content are posted daily on the Web, including textual, spatial and temporal information. Exploiting this content to detect, analyze and monitor events and topics that have a potentially large span in space and time requires eficient retrieval and ranking based on criteria including all three dimensions. In this paper, we introduce a novel type of spatial-temporal-keyword query that combines keyword search with the task of maximizing the spatio-temporal coverage and diversity of the returned top-k results. We first describe a baseline algorithm based on related search results diversification problems. Then, we develop an eficient approach which exploits a hybrid spatial-temporal-keyword index to drastically reduce query execution time. To that end, we extend two state-of-the-art indices for top-k spatio-textual queries and describe how our proposed approach can be applied on top of them. We evaluate the efficiency of our algorithms by conducting experiments on two large, real-world datasets containing geo tagged tweets and photos.
Author(s)
Mehta, P.
Skoutas, D.
Sacharidis, D.
Voisard, A.
Hauptwerk
24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Proceedings
Konferenz
International Conference on Advances in Geographic Information Systems (GIS) 2016
Thumbnail Image
DOI
10.1145/2996913.299694
Language
English
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