图 书 馆
使用笔记本电脑进行大规模基于规则的推理Large Scale Rule-Based Reasoning Using a Laptop |
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| 课程网址: | http://videolectures.net/eswc2015_peters_reasoning/ |
| 主讲教师: | Martin Peters |
| 开课单位: | 多特蒙德学院 |
| 开课时间: | 2015-07-15 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Although recent developments have shown that it is possible to reason over large RDF datasets with billions of triples in a scalable way, the reasoning process can still be a challenging task with respect to the growing amount of available semantic data. By now, reasoner implementations that are able to process large scale datasets usually use a MapReduce based implementation that runs on a cluster of computing nodes. In this paper we address this circumstance by identifying the resource consuming parts of a reasoner process and providing a solution for a more efficient implementation in terms of memory consumption. As a basis we use a rule-based reasoner concept from our previous work. In detail, we are going to introduce an approach for a memory efficient RETE algorithm implementation. Furthermore, we introduce a compressed triple-index structure that can be used to identify duplicate triples and only needs a few bytes to represent a triple. Based on these concepts we show that it is possible to apply all RDFS rules to more than 1 billion triples on a single laptop reaching a throughput, that is comparable or even higher than state of the art MapReduce based reasoner. Thus, we show that the resources needed for large scale lightweight reasoning can massively be reduced. |
| 关 键 词: | 语义数据; 资源消耗; 识别重复 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-03-06：chenjy |
| 最后编审: | 2023-03-06：chenjy |
| 阅读次数: | 26 |