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Journal Articles Journal on Data Semantics Year : 2018

Multi-Query Optimization on RSS Feeds

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Fekade Getahun

Abstract

RSS feeds are text-content rich, semantically heterogeneous, and contain dynamic XML elements streamed in asynchronous and pull strategies. Hence, for efficient retrieval of RSS feeds, semantic-aware querying operators have been proposed in the literature (Getahun and Chbeir in Inf Sci 237(237):313\textendash342, 2013). However, it is commonly admitted that the use of semantic information would improve, on one hand, the relevance of query result but, on the other hand, at the cost of degrading the efficiency and the performance of the system. To benefit from query execution on semantic information while keeping the efficiency of the system, we propose here a multi-query optimization approach for semantic RSS feed queries. Our approach processes queries by examining the semantic relationship between them and their corresponding windows. It generates a multi-query chain for queries using their window relations for faster execution at runtime. In addition, we propose an operator called quickDrop for semantic load shedding to gracefully decrease irrelevant data load. To validate the proposed approach, we developed a prototype and conducted a set of experiments. The obtained results show that the use of our approach significantly improves the performance of the system. \textcopyright 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
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Dates and versions

hal-01906797 , version 1 (27-10-2018)

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Fekade Getahun, Richard Chbeir. Multi-Query Optimization on RSS Feeds. Journal on Data Semantics, 2018, 7 (1), pp.47-64. ⟨10.1007/S13740-018-0085-3⟩. ⟨hal-01906797⟩

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