图 书 馆
谓词展开的同义词分析Synonym Analysis for Predicate Expansion |
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| 课程网址: | http://videolectures.net/eswc2013_abedjan_synonym/ |
| 主讲教师: | Laura Hollink |
| 开课单位: | 美国数学与信息中心 |
| 开课时间: | 2013-07-08 |
| 课程语种: | 英语 |
| 中文简介: |  尽管有统一的数据模型，例如结构级别的资源描述框架（Rdf）和相应的查询语言Sparql，但链接开放数据的集成和使用在语义级别上面临着重大的异构性挑战。本体概念和类属性的错误使用阻碍了机器可读性和知识发现的目标。例如，与某位艺术家一起搜索电影的用户不能依赖单个给定的属性艺术家，因为某些电影可能会通过谓词加注链接到该艺术家。另外，数据消费者的信息需求可能并不总是很清楚，并且她对给定模式的解释可能与本体工程师或数据发布者的意图不同。因此，有必要在查询编制过程中为用户提供支持，或者通过谓词扩展来合并隐式相关的事实。为此，我们介绍了一种用于谓词扩展的数据驱动同义词发现算法。为此，我们将算法应用于各种数据集，充分评估了不同策略和基于规则的技术。 |
| 课程简介: | Despite unified data models, such as the Resource Description Framework (Rdf) on structural level and the corresponding query language Sparql, the integration and usage of Linked Open Data faces major heterogeneity challenges on the semantic level. Incorrect use of ontology concepts and class properties impede the goal of machine readability and knowledge discovery. For example, users searching for movies with a certain artist cannot rely on a single given property artist, because some movies may be connected to that artist by the predicate starring. In addition, the information need of a data consumer may not always be clear and her interpretation of given schemata may differ from the intentions of the ontology engineer or data publisher. It is thus necessary to either support users during query formulation or to incorporate implicitly related facts through predicate expansion. To this end, we introduce a data-driven synonym discovery algorithm for predicate expansion. We applied our algorithm to various data sets as shown in a thorough evaluation of different strategies and rule-based techniques for this purpose. |
| 关 键 词: | 数据模型; 数据集; 数据集成 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2021-03-24：zyk |
| 最后编审: | 2021-03-24：zyk |
| 阅读次数: | 47 |