Enriching news events with meta-knowledge information

Enriching news events with meta-knowledge information
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用元知识信息丰富新闻事件

DOI:
10.1007/s10579-016-9344-9
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发表时间:
2016
影响因子:
2.7
通讯作者:
Thompson P
Thompson P
中科院分区:
计算机科学4区
文献类型:
--
作者:
Thompson P

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鉴于以数字化文本形式提供的大量数据,提供允许用户从不断增长的潜在重要文档中提取相关信息的机制非常重要。文本挖掘技术可以通过其自动提取关联事件描述的能力提供帮助,关联事件描述将实体与文本中描述的情况联系起来。然而,正确和完整的解释这些事件的描述是不可能的,如果不考虑额外的上下文信息往往存在于周围的文字。这些信息,我们称之为元知识,可以包括(但不限于)事件的模态、主观性、来源、极性和特异性。我们已经开发了一个专门为新闻事件量身定制的元知识注释方案,其中包括六个方面的事件解释。我们已经将此注释方案的ACE 2005语料库,其中包含599个文件,从各种书面和口头新闻来源。我们还确定和注释的单词和短语唤起不同类型的元知识。注释语料库的评价显示高水平的注释者之间的协议的五个元知识属性,和第六属性的协议的中等水平。通过对标注语料的分析,进一步揭示了不同类型元知识的表达机制、相对频率和相互关系。
Given the vast amounts of data available in digitised textual form, it is important to provide mechanisms that allow users to extract nuggets of relevant information from the ever growing volumes of potentially important documents. Text mining techniques can help, through their ability to automatically extract relevanteventdescriptions, which link entities with situations described in the text. However, correct and complete interpretation of these event descriptions is not possible without considering additional contextual information often present within the surrounding text. This information, which we refer to asmeta-knowledge, can include (but is not restricted to) the modality, subjectivity, source, polarity and specificity of the event. We have developed a meta-knowledge annotation scheme specifically tailored for news events, which includes six aspects of event interpretation. We have applied this annotation scheme to the ACE 2005 corpus, which contains 599 documents from various written and spoken news sources. We have also identified and annotated the words and phrases evoking the different types of meta-knowledge. Evaluation of the annotated corpus shows high levels of inter-annotator agreement for five meta-knowledge attributes, and moderate level of agreement for the sixth attribute. Detailed analysis of the annotated corpus has revealed further insights into the expression mechanisms of different types of meta-knowledge, their relative frequencies and mutual correlations.
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