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Explaining and Querying Knowledge Graphs by Relatedness

Summary: RECAP explains relatedness between KG entities and enables a query-by-relatedness paradigm. No preprocessing needed; merges data across multiple KGs via SPARQL, with local refinement, enabling cross-domain use on endpoints. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11484
Venue
VLDB
Year
2017
Pagerank
5.7971866e-05
Overall Rank
4,963 | 65.48%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
6,011 X2Q: Your Personal Example-based Graph Explorer 2018 VLDB 5.2415551e-05
9,572 Discovering Diversified Paths in Knowledge Bases 2018 VLDB 4.3254101e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Rank Cited Paper Year Venue Pagerank
3,684 SPARQLByE: Querying RDF data by example 2016 VLDB 6.8465042e-05
4,063 REX: Explaining Relationships between Entity Pairs 2012 VLDB 6.4825871e-05
4,422 Interactive Join Query Inference with JIM 2014 VLDB 6.2008389e-05
4,686 Discovering and Exploring Relations on the Web 2012 VLDB 5.9987806e-05
7,295 Searching with XQ: the eXemplar Query Search Engine 2014 SIGMOD 4.7728968e-05
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