关联数据及其应用现状综述

自主、异类、异构和分布的海量数据间的语义关联一直是知识组织和知识发现的核心问题,关联数据(Linked Data)技术的出现为此提供一种轻型、渐增化、可伸缩和可扩展的动态机制。基于对大量文献的梳理和分析,描述Linked Data的原则与技术体系,介绍Linked Data发布、Link浏览器、Linked Data搜索引擎、Link更新维护等核心技术,简要介绍若干典型应用,提出在具体领域实施Linked Data应用的关键挑战。     

基于Vitro构建专业领域知识应用环境

以中国科学院国家科学图书馆开展专业领域知识应用环境建设为背景,通过对Vitro组成结构和功能特征的分析,提出基于Vitro的专业领域知识应用环境平台的设计方案,并介绍平台系统实现中对Vitro本地化应用开发的主要方法。     

DC元数据年度进展（2010）

文章介绍了都柏林元数据（DC）2010年年会基本情况,以及DC管理机构DCMI近一年的研究成果,其中主要是对关联数据理论与实践的研究,以及在关联数据和互操作环境下对DCMI推荐文档进行的相关审议和修订。文章也总结了DCMI过去一年工作与组织进展,探索了DCMI的发展方向。     

Using semantic similarity to reduce wrong labels in distant supervision for relation extraction

Distant supervision (DS) has the advantage of automatically generating large amounts of labelled training data and has been widely used for relation extraction. However, there are usually many wrong labels in the automatically labelled data in distant supervision (Riedel, Yao, & McCallum, 2010). This paper presents a novel method to reduce the wrong labels. The proposed method uses the semantic Jaccard with word embedding to measure the semantic similarity between the relation phrase in the knowledge base and the dependency phrases between two entities in a sentence to filter the wrong labels. In the process of reducing wrong labels, the semantic Jaccard algorithm selects a core dependency phrase to represent the candidate relation in a sentence, which can capture features for relation classification and avoid the negative impact from irrelevant term sequences that previous neural network models of relation extraction often suffer. In the process of relation classification, the core dependency phrases are also used as the input of a convolutional neural network (CNN) for relation classification. The experimental results show that compared with the methods using original DS data, the methods using filtered DS data performed much better in relation extraction. It indicates that the semantic similarity based method is effective in reducing wrong labels. The relation extraction performance of the CNN model using the core dependency phrases as input is the best of all, which indicates that using the core dependency phrases as input of CNN is enough to capture the features for relation classification and could avoid negative impact from irrelevant terms.     

大学英语词汇教学策略

词汇教学在大学英语教学中至关重要.目前词汇教学存在种种误区,成为制约学生学好英语的障碍.本文探讨了语境策略、精加工策略、语义场策略、词块记忆策略和元认知策略,以改进大学英语词汇教学现状.     

新兴“X活族”词语及其语用修辞价值

“X活族”新词是指“快活族”、“慢活族”、“乐活族”这样新出现的带“活族”的词语。“X活族”新词的句法和语义构成比较复杂;语用上具有继承性与创新性、二次创新和非常规性、音译兼意译,洋为中用的特点;修辞上巧用对比、转喻和概念整合手段,具有形象创新、词约义丰、直指本质以及陌生化的功能。“X活族”新词的涌现,是语言和社会共同作用的结果。     

现代汉语的“一点儿”和“有点儿”——从对外汉语教学说起

从对外汉语教学的实践出发,我们发现了留学生容易对“一点儿”和“有点儿”的用法混淆,因此有必要对现代汉语中“一点儿”和“有点儿”的混淆成因进行理论上的分析并进一步指出二者在用法和语义上细微的差异。     

A''da''m-自补有向循环图

A'da'm自补有向循环图是循环图中很独特的一类,有很好应用前景,特别在网络时代的今天,A'da'm自补有向循环图更具它独特的魅力。但是,A'da'm自补有向循环图一般结构很难给出,本文给出了三类自补有向循环图。     

预设理论研究及应用举隅

预设本是源于哲学领域的概念,后来逐步引起语言学家的重视.在语言学范围内.预设的研究可以分为语义预设和语用预设.本文将从两者各自的特点出发进行比较分析,最后得出两者应该以互补的形式共同研究预设.文章还将预设与语篇应用联系起来,分别就广告、标语、戏剧和幽默语篇从预设的角度进行浅析.     

汉语并列短语标记隐现的认知研究

汉语中的并列短语的标记手段有两种：无标记和有标记,它们的使用并不是任意的,而是有理可据的。该文用认知语言学理论论证：标记的隐现主要相关于并列项之间语义的亲近性和其他一些制约条件。