图 书 馆
waterflowl：一个紧凑的、自索引的、支持推理的不可变RDF存储WaterFowl: a Compact, Self-indexed and Inference-enabled immutable RDF Store |
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| 课程网址: | http://videolectures.net/eswc2014_cure_water_fowl/ |
| 主讲教师: | Olivier Curé |
| 开课单位: | 巴黎大学 |
| 开课时间: | 2014-07-30 |
| 课程语种: | 英语 |
| 中文简介: |  在本文中，我们介绍了WaterFowl，这是一种用于存储RDF三元组的新颖方法，可通过压缩解决可伸缩性问题。我们原型的体系结构主要基于使用简洁的数据结构，从而能够以自索引，紧凑的方式表示三元组，而无需在查询回答时进行解压缩。此外，由于本体概念和属性的优化编码（不需要完整的推理实现或查询重构），因此它可以有效地支持RDF和RDFS包含机制。这种方法意味着在数据准备过程的早期就区分知识库的术语和主张部分，即：在将数据存储到我们的结构中之前对其进行预处理。本文描述了我们系统的体系结构，并提出了通过对不同数据集进行评估获得的一些初步结果。 |
| 课程简介: | In this paper we present WaterFowl, a novel approach for the storage of RDF triples that addresses scalability issues through compression. The architecture of our prototype, largely based on the use of succinct data structures, enables the representation of triples in a self-indexed, compact manner without requiring decompression at query answering time. Moreover, it is adapted to efficiently support RDF and RDFS entailment regimes thanks to an optimized encoding of ontology concepts and properties that does not require a complete inference materialization or query reformulation. This approach implies to make a distinction between the terminological and the assertional components of the knowledge base early in the process of data preparation, i:e: preprocessing the data before storing it in our structures. The paper describes our system's architecture and presents some preliminary results obtained from evaluations on di erent datasets. |
| 关 键 词: | 存储RDF; 优化编码; 数据结构; 数据存储 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2021-05-12：zyk |
| 最后编审: | 2021-05-26：zyk |
| 阅读次数: | 50 |