Retrieving Regions of Interest for User Exploration
Data(s) |
2014
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Resumo |
We consider an application scenario where points of interest (PoIs) each have a web presence and where a web user wants to iden- tify a region that contains relevant PoIs that are relevant to a set of keywords, e.g., in preparation for deciding where to go to conve- niently explore the PoIs. Motivated by this, we propose the length- constrained maximum-sum region (LCMSR) query that returns a spatial-network region that is located within a general region of in- terest, that does not exceed a given size constraint, and that best matches query keywords. Such a query maximizes the total weight of the PoIs in it w.r.t. the query keywords. We show that it is NP- hard to answer this query. We develop an approximation algorithm with a (5 + ǫ) approximation ratio utilizing a technique that scales node weights into integers. We also propose a more efficient heuris- tic algorithm and a greedy algorithm. Empirical studies on real data offer detailed insight into the accuracy of the proposed algorithms and show that the proposed algorithms are capable of computingresults efficiently and effectively. |
Formato |
application/pdf |
Identificador | |
Idioma(s) |
eng |
Direitos |
info:eu-repo/semantics/openAccess |
Fonte |
Cao , X , Cong , G , Jensen , C S & Yiu , M L 2014 , Retrieving Regions of Interest for User Exploration . in Proceedings of the VLDB Endowment (PVLDB) . vol. 7 , pp. 733-744 , International Conference on Very Large Data Bases , Hangzhou , China , 1-5 September . |
Tipo |
contributionToPeriodical |