Set Expansion using Sibling Relations between Semantic Categories

Sho Takase, Naoaki Okazaki, Kentaro Inui
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引用次数: 1

Abstract

Most set expansion algorithms assume to acquire new instances of different semantic categories independently even when we have seed instances of multiple semantic categories. However, in the setting of set expansion with multiple semantic categories, we might leverage other types of prior knowledge about semantic categories. In this paper, we present a method of set expansion when ontological information related to target semantic categories is available. More specifically, the proposed method makes use of sibling relations between semantic categories as an additional type of prior knowledge. We demonstrate the effectiveness of sibling relations in set expansion on the dataset in which instances and sibling relations are extracted from Wikipedia in a semi-automatic manner.
使用语义类别之间的兄弟关系设置扩展
大多数集展开算法假设,即使我们有多个语义类别的种子实例,也能独立获取不同语义类别的新实例。然而,在具有多个语义类别的集合展开设置中,我们可能会利用其他类型的关于语义类别的先验知识。本文提出了一种与目标语义范畴相关的本体信息可用时集合展开的方法。更具体地说,该方法利用语义类别之间的兄弟关系作为一种额外的先验知识类型。我们在以半自动方式从维基百科中提取实例和兄弟关系的数据集上证明了兄弟关系在集扩展中的有效性。
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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