Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/105001
Title: Retrieving regions of interest for user exploration
Authors: Cao, Xin
Cong, Gao
Jensen, Christian S.
Yiu, Man Lung
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2014
Source: Cao, X., Cong, G., Jensen, C. S., & Yiu, M. L. (2014). Retrieving regions of interest for user exploration. VLDB endowment, 7(9), 733-744. doi: 10.14778/2732939.2732946
Series/Report no.: Proceedings of the VLDB endowment
Abstract: 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 + ε) 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 computing results efficiently and effectively.
URI: https://hdl.handle.net/10356/105001
http://hdl.handle.net/10220/20433
DOI: 10.14778/2732939.2732946
Rights: © 2014 VLDB Endowment. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/. Obtain permission prior to any use beyond those covered by the license. Contact copyright holder by emailing info@vldb.org. Articles from this volume were invited to present their results at the 40th International Conference on Very Large Data Bases, September 1st - 5th 2014, Hangzhou, China.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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