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Flexible query answering on graph-modeled data

Published: 24 March 2009 Publication History

Abstract

The largeness and the heterogeneity of most graph-modeled datasets in several database application areas make the query process a real challenge because of the lack of a complete knowledge of the vocabulary used, as well as of the information about the structural relationships between the data.
To overcome these problems, flexible query answering capabilities are an essential need. In this paper we present a general model for supporting approximate queries on graph-modeled data. Approximation is both on the vocabularies and the structure. The model is general in that it is not bound to a specific graph data model, rather it gracefully accommodates labeled directed/undirected data graphs with labeled/unlabeled edges. The query answering principles underlying the model are not compelled to a specific data graph, instead they are founded on properties inferable from the data model the data graph conforms to. We complement the work with a ranking model to deal with data approximations and with an efficient top-k retrieval algorithm which smartly accesses ad-hoc data structures and generates the most promising answers in an order correlated with the ranking measures. Experimental results prove the good effectiveness and efficiency of our proposal on different real world datasets.

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  • (2022)Optimisation Techniques for Flexible SPARQL QueriesACM Transactions on the Web10.1145/353285516:4(1-44)Online publication date: 16-Nov-2022
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  • (2019)Approximate Querying for the Property Graph Language Cypher2019 IEEE International Conference on Big Data (Big Data)10.1109/BigData47090.2019.9005466(617-622)Online publication date: Dec-2019
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cover image ACM Other conferences
EDBT '09: Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
March 2009
1180 pages
ISBN:9781605584225
DOI:10.1145/1516360
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 March 2009

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EDBT/ICDT '09
EDBT/ICDT '09: EDBT/ICDT '09 joint conference
March 24 - 26, 2009
Saint Petersburg, Russia

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Overall Acceptance Rate 7 of 10 submissions, 70%

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Cited By

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  • (2022)Optimisation Techniques for Flexible SPARQL QueriesACM Transactions on the Web10.1145/353285516:4(1-44)Online publication date: 16-Nov-2022
  • (2020)Approximate Query Answering Based on Topological Neighborhood and Semantic Similarity in OpenStreetMapIEEE Access10.1109/ACCESS.2020.29922028(87011-87030)Online publication date: 2020
  • (2019)Approximate Querying for the Property Graph Language Cypher2019 IEEE International Conference on Big Data (Big Data)10.1109/BigData47090.2019.9005466(617-622)Online publication date: Dec-2019
  • (2018)Applications of Flexible Querying to Graph DataGraph Data Management10.1007/978-3-319-96193-4_4(97-142)Online publication date: 1-Nov-2018
  • (2018)Fuzzy Preference Queries to NoSQL Graph DatabasesNoSQL Data Models10.1002/9781119528227.ch6(167-201)Online publication date: 6-Aug-2018
  • (2017)From Data Integration to Big Data IntegrationA Comprehensive Guide Through the Italian Database Research Over the Last 25 Years10.1007/978-3-319-61893-7_3(43-59)Online publication date: 31-May-2017
  • (2016)Answering Approximate Queries Over XML DataIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2015.245316824:2(288-305)Online publication date: Apr-2016
  • (2016)Approximation and relaxation of semantic web path queriesWeb Semantics: Science, Services and Agents on the World Wide Web10.1016/j.websem.2016.08.00140:C(1-21)Online publication date: 1-Oct-2016
  • (2015)Considering User Intention in Differential Graph QueriesJournal of Database Management10.4018/JDM.201507010226:3(21-40)Online publication date: 1-Jul-2015
  • (2015)Relaxation of subgraph queries delivering empty resultsProceedings of the 27th International Conference on Scientific and Statistical Database Management10.1145/2791347.2791382(1-12)Online publication date: 29-Jun-2015
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