图 书 馆
链接数据词汇化的必要性The Need for Lexicalization of Linked Data |
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| 课程网址: | http://videolectures.net/w3cworkshop2012_mccrae_data/ |
| 主讲教师: | John Philip McCrae |
| 开课单位: | 爱尔兰国立大学 |
| 开课时间: | 2012-06-12 |
| 课程语种: | 英语 |
| 中文简介: |  尽管链接的数据通常独立于语言，但是此数据的解释要求使用自然语言标识符，才能对最终用户有意义。对于链接数据的许多应用，尤其是在多语言环境中，有必要超越简单的字符串标签，并提供链接数据实体的词汇化的更丰富描述，例如通过生成数据的自然语言描述。为了解决这一差距，我们提出了一个模型，我们称为Lemon（本体模型），该模型在语义和句法层面上都可以区分标签。 Lemon的目标是在现有的表示词汇信息的模型的基础上进行构建，但要简洁，描述性和模块化。此外，该模型旨在弥合以RDF（S）和OWL等格式描述的现有链接数据云与快速增长的语言链接数据云之间的差距，在该语言云中已经存在大量的多语言数据。我将展示一些示例，这些示例说明了如何在不花费大量精力的情况下将协作编辑技术与Lemon模型一起使用来创建此类数据，以及如何将其应用于诸如通过链接的数据回答自然语言问题之类的任务。 |
| 课程简介: | While linked data is frequently independent of language, the interpretation of this data requires natural language identifiers in order to be meaningful to the end user. For many applications of linked data, especially in multilingual contexts, it is necessary to go beyond the simple string label and provide a richer description of the lexicalization of the linked data entities, for example by generating natural language descriptions of the data. To address this gap we have proposed a model, which we call Lemon (Lexicon Model for Ontologies), that distinguishes the labels at both the semantic and syntactic levels. Lemon aims to build on existing models for representing lexical information, but is concise, descriptive and modular. Furthermore, this model is designed to bridge the gap between the existing linked data cloud, described in formats such as RDF(S) and OWL and the rapidly growing linguistic linked data cloud, where a significant amount of multilingual data already exists. I will show examples of how we can use collaborative editing techniques with the Lemon model to create such data without significant effort and how this can be applied to tasks such as answering natural language questions over linked data. |
| 关 键 词: | 链接数据; 多语言数据; 协作编辑 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-11-19：zyk |
| 最后编审: | 2020-11-19：zyk |
| 阅读次数: | 67 |