Entity Resolution Using Inferred Relationships and Behavior

被引：0

作者：

Mugan, Jonathan ^{[1
]}

Chari, Ranga ^{[1
]}

Hitt, Laura ^{[1
]}

McDermid, Eric ^{[1
]}

Sowell, Marsha ^{[1
]}

Qu, Yuan ^{[1
]}

Coffman, Thayne ^{[2
]}

机构：

[1] 21CT Inc, Austin, TX 78730 USA

[2] RGM Advisors LLC, Austin, TX USA

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2014年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a method for entity resolution that infers relationships between observed identities and uses those relationships to aid in mapping identities to underlying entities. We also introduce the idea of using graphlets for entity resolution. Graphlets are collections of small graphs that can be used to characterize the "role" of a node in a graph. The idea is that graphlets can provide a richer set of features to characterize identities. We validate our method on standard author datasets, and we further evaluate our method using data collected from Twitter. We find that inferred relationships and graphlets are useful for entity resolution.

引用

页码：555 / 560

页数：6

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