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RDF知识图的有效搜索

Effective Searching of RDF Knowledge Graphs
课程网址: http://videolectures.net/iswc2018_arnaout_effective_rdf_graphs/  
主讲教师: Hiba Arnaout
开课单位: 马克斯·普朗克信息学研究所
开课时间: 2018-11-22
课程语种: 英语
中文简介:
RDF知识图通常使用三重模式查询进行搜索。通常,三重模式查询会返回太多或太少的结果,使得用户很难找到与其信息需求相关的答案。为了解决这一问题,我们提出了一个有效搜索RDF知识图的通用框架。我们的框架扩展了搜索到的知识图和带有关键字的三模式查询,以允许用户形成更广泛的查询。此外,它提供基于统计机器翻译的结果排名,并执行自动查询放松以提高查询召回率。最后,我们还定义了RDF数据设置中结果多样性的概念,并提供了使用最大边际相关性使RDF搜索结果多样化的机制。我们使用对DBpedia(一个大型且真实的RDF知识图)的各种精心设计的用户研究来评估我们的检索框架的有效性。
课程简介: RDF knowledge graphs are typically searched using triple-pattern queries. Often, triple-pattern queries will return too many or too few results, making it difficult for users to find relevant answers to their information needs. To remedy this, we propose a general framework for effective searching of RDF knowledge graphs. Our framework extends both the searched knowledge graph and triple-pattern queries with keywords to allow users to form a wider range of queries. In addition, it provides result ranking based on statistical machine translation, and performs automatic query relaxation to improve query recall. Finally, we also define a notion of result diversity in the setting of RDF data and provide mechanisms to diversify RDF search results using Maximal Marginal Relevance. We evaluate the effectiveness of our retrieval framework using various carefully-designed user studies on DBpedia, a large and real-world RDF knowledge graph.
关 键 词: RDF知识图; 三重模式查询; 有效搜索RDF知识图; RDF搜索结果多样化的机制
课程来源: 视频讲座网
数据采集: 2022-12-29:cyh
最后编审: 2022-12-29:cyh
阅读次数: 22