EVIN: Building a Knowledge Base of Events

被引：12

作者：

Kuzey, Erdal ^{[1
]}

Weikum, Gerhard ^{[1
]}

机构：

[1] Max Planck Inst Informat, Saarbrucken, Germany

来源：

WWW'14 COMPANION: PROCEEDINGS OF THE 23RD INTERNATIONAL CONFERENCE ON WORLD WIDE WEB | 2014年

关键词：

D O I：

10.1145/2567948.2577009

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 EVIN: a system that extracts named events from news articles, reconciles them into canonicalized events, and organizes them into semantic classes to populate a knowledge base. EVIN exploits different kinds of similarity measures among news, referring to textual contents, entity occurrences, and temporal ordering. These similarities are captured in a multi-view attributed graph. To distill canonicalized events, EVIN coarsens the graph by iterative merging based on a judiciously designed loss function. To infer semantic classes of events, EVIN uses statistical language models. EVIN provides a GUI that allows users to query the constructed knowledge base of events, and to explore it in a visual manner.

引用

页码：103 / 106

页数：4

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