A Probabilistic Model for Linking Named Entities in Web Text with Heterogeneous Information Networks

Summary: SHINE is the first probabilistic model to link web-text named entities to heterogeneous information networks. Entity popularity and an entity object model built from meta-path constrained random walks; meta-path weights learned by EM without training data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 4806
Venue: SIGMOD
Year: 2014
Pagerank: 4.4258255e-05
Overall Rank: 8,944 | 37.78%
DOI: 10.1145/2588555.2593676

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
8,005	Online Topic-Aware Entity Resolution Over Incomplete Data Streams	2021	SIGMOD	4.6081461e-05
9,136	TextCube: Automated Construction and Multidimensional Exploration	2019	VLDB	4.3881065e-05
9,251	Joint Open Knowledge Base Canonicalization and Linking	2021	SIGMOD	4.3690661e-05
11,724	ZigZag: Supporting Similarity Queries on Vector Space Models	2018	SIGMOD	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
768	PathSim: Meta Path-Based Top-K Similarity Search in Heterogeneous Information Networks	2011	VLDB	0.00016919065
2,405	Linking Temporal Records	2011	VLDB	8.8815018e-05
2,847	Building, Maintaining, and Using Knowledge Bases: A Report from the Trenches	2013	SIGMOD	8.0224023e-05
3,545	DBLP — Some Lessons Learned	2009	VLDB	6.989355e-05

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7,600	Heterogeneous Information Networks: the Past, the Present, and the Future	2022	VLDB	4.6990255e-05
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