使用Map/Reduce框架促进联邦查询的本体驱动查询扩展

N. Alipanah, L. Khan, B. Thuraisingham
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引用次数: 22

摘要

鉴于对高度分布式和联邦体系结构的需求,鲁棒的查询扩展对信息检索的性能有很大的影响。我们的目标是使用不同的加权技术确定本体驱动的查询扩展术语。为此,我们考虑每个单独的本体和用户查询关键字,使用包括between Measure (BM)和semantic Similarity Measure (SSM)在内的一系列语义度量来确定基本扩展项(BET)。提出了一种计算本体图中所有最短路径的Map/Reduce分布式算法。Map/Reduce算法将大大提高大型本体的BET计算效率。
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Ontology-Driven Query Expansion Using Map/Reduce Framework to Facilitate Federated Queries
In view of the need for a highly distributed and federated architecture, a robust query expansion has great impact on the performance of information retrieval. We aim to determine ontology-driven query expansion terms using different weighting techniques. For this, we consider each individual ontology and user query keywords to determine the Basic Expansion Terms (BET) using a number of semantic measures including Betweenness Measure (BM) and Semantic Similarity Measure (SSM). We propose a Map/Reduce distributed algorithm for calculating all the shortest paths in ontology graph. Map/Reduce algorithm will improve considerably the efficiency of BET calculation for large ontologies.
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