Querying linked ontological data through distributed summarization

Achille Fokoue, Felipe Meneguzzi, Murat Sensoy, Jeff Z Pan

Research output: Contribution to conferencePaper

9 Citations (Scopus)

Abstract

As the semantic web expands, ontological data becomes distributed over a large network of data sources on the Web. Consequently, evaluating queries that aim to tap into this distributed semantic database necessitates the ability to consult multiple data sources efficiently. In this paper, we propose methods and heuristics to efficiently query distributed ontological data based on a series of properties of summarized data. In our approach, each source summarizes its data as another RDF graph, and relevant section of these summaries are merged and analyzed at query evaluation time. We show how the analysis of these summaries enables more efficient source selection, query pruning and transformation of expensive distributed joins into local joins.
Original languageEnglish
Pages31-
Number of pages7
Publication statusPublished - Jul 2012
EventTwenty-Sixth AAAI Conference on Artificial Intelligence - Toronto, Canada
Duration: 22 Jul 201226 Jul 2012

Conference

ConferenceTwenty-Sixth AAAI Conference on Artificial Intelligence
CountryCanada
CityToronto
Period22/07/1226/07/12

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Fokoue, A., Meneguzzi, F., Sensoy, M., & Pan, J. Z. (2012). Querying linked ontological data through distributed summarization. 31-. Paper presented at Twenty-Sixth AAAI Conference on Artificial Intelligence, Toronto, Canada.