Multi-example search in rich information graphs

Matteo Lissandrini, Davide Mottin, Themis Palpanas, Yannis Velegrakis

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Abstract

    In rich information spaces, it is often hard for users to formally specify the characteristics of the desired answers, either due to the complexity of the schema or of the query language, or even because they do not know exactly what they are looking for. Exemplar queries constitute a query paradigm that overcomes those problems, by allowing users to provide examples of the elements of interest in place of the query specification. In this paper, we propose a general approach where the user-provided example can comprise several partial specification fragments, where each fragment describes only one part of the desired result. We provide a formal definition of the problem, which generalizes existing formulations for both the relational and the graph model. We then describe exact algorithms for its solution for the case of information graphs, as well as top-k algorithms. Experiments on large real datasets demonstrate the effectiveness and efficiency of the proposed approach.

    Original languageEnglish
    Title of host publicationProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
    PublisherIEEE
    Pages809-820
    Number of pages12
    ISBN (Electronic)9781538655207
    DOIs
    Publication statusPublished - 24 Oct 2018
    Event34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, France
    Duration: 16 Apr 201819 Apr 2018

    Conference

    Conference34th IEEE International Conference on Data Engineering, ICDE 2018
    Country/TerritoryFrance
    CityParis
    Period16/04/1819/04/18

    Keywords

    • Exemplar queries
    • Graph Search
    • Knowledge Graph

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