Linking, integrating, and translating entities via iterative graph matching

Taesung Lee, Seung-won Hwang
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引用次数: 2

Abstract

Entity tasks, such as linking, integration, and translation, are crucial for many search and NLP applications. For this purposed entity graphs have been manually built or automatically harvested. In this paper, we survey existing approaches abstracting these problems into a graph-based iterative matching on a pair of entity graphs.
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通过迭代图匹配链接、集成和翻译实体
实体任务,如链接、集成和翻译,对于许多搜索和NLP应用程序至关重要。为此,需要手动构建或自动获取实体图。本文综述了将这些问题抽象为实体图对上基于图的迭代匹配的现有方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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