Category-associated collocative concept primitives extraction

Zhejie Chi, Quan Zhang
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Abstract

Collocation is studied as an essential linguistic phenomenon in traditional natural language processing. Similarity, collocative concept primitives are introduced in HNC Concept Primitive Space to present the concept primitive pair co-occurring frequently. Collocative concept primitives can be studied with categories together as concept primitives usually contain category information. To explore the collocation phenomenon in the field of HNC and apply collocative information to language processing, this paper presents a two-stage approach to extract category-associated collocative concept primitives from a classification corpus. By conducting collocative concept primitives extraction in each sub-category corpus and carrying out category-associated collocative concept primitives extraction in the summarized corpus, we generate a category-associated collocative concept primitives list for each category. Our experiments show the items we extract are consistent with the reality and are of significance.
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与类别相关的并置概念原语提取
在传统的自然语言处理中,搭配是一种重要的语言现象。在HNC概念原语空间中引入相似性、搭配性概念原语来表示频繁共现的概念原语对。搭配概念原语可以和范畴一起研究,因为概念原语通常包含范畴信息。为了探索HNC领域的搭配现象,并将搭配信息应用于语言处理,本文提出了一种从分类语料库中提取与类别相关的搭配概念原语的两阶段方法。通过在每个子类别语料库中进行搭配概念原语提取,并在汇总的语料库中进行与类别相关的搭配概念原语提取,生成每个类别的与类别相关的搭配概念原语列表。实验表明,我们提取的项目与现实相符,具有一定的意义。
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