GroupFinder: A New Approach to Top-K Point-of-Interest Group Retrieval

Summary: Introduces top-k retrieval of nearby groups of PoIs matching keyword and spatial queries, rather than individual locations. Maps group semantics to user-facing parameters and uses efficient search to avoid combinatorial explosion in practical settings. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID: 10767
Venue: VLDB
Year: 2013
Pagerank: 5.093636e-05
Overall Rank: 12,265 | 15.86%
DOI: 10.14778/2536274.2536300

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

1. Kenneth S. Bøgh (Aarhus University)
2. Anders Skovsgaard (Aarhus University)
3. Christian S. Jensen (Aarhus University)

BibTeX Citation

@article{bgh_vldb13,
        title = {{GroupFinder: A New Approach to Top-K Point-of-Interest Group Retrieval}},
        author = {Bøgh, Kenneth S. and Skovsgaard, Anders and Jensen, Christian S.},
        journal = {PVLDB},
        series = {{VLDB} '13},
        volume = {6},
        number = {12},
        pages = {1226--1229},
        doi = {10.14778/2536274.2536300},
        url = {https://doi.org/10.14778/2536274.2536300},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
8,823	Querying Geo-Textual Data: Spatial Keyword Queries and Beyond	2016	SIGMOD	5.3624668e-05

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
1,441	Efficient Processing of Top-k Spatial Preference Queries	2011	VLDB	0.00010778831
4,486	Collective Spatial Keyword Querying	2011	SIGMOD	6.6693992e-05
13,671	SWORS: A System for the Efficient Retrieval of Relevant Spatial Web Objects	2012	VLDB	-

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