Example-based Search: A new frontier for exploratory search

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

DOI

  • Matteo Lissandrini, Aalborg University Hospital
  • ,
  • Davide Mottin
  • Themis Palpanas, Universite Paris 5
  • ,
  • Yannis Velegrakis, Utrecht University, Utrecht

Exploration is one of the primordial ways to accrue knowledge about the world and its nature. As we accumulate, mostly automatically, data at unprecedented volumes and speed, our datasets have become complex and hard to understand. In this context, exploratory search provides a handy tool for progressively gather the necessary knowledge by starting from a tentative query that can provide cues about the next queries to issue. An exploratory query should be simple enough to avoid complicate declarative languages (such as SQL) and convoluted mechanism, and at the same time retain the flexibility and expressiveness required to express complex information needs. Recently, we have witnessed a rediscovery of the so called example-based methods, in which the user, or the analyst circumvent query languages by using examples as input. This shift in semantics has led to a number of methods receiving as query a set of example members of the answer set. The search system then infers the entire answer set based on the given examples and any additional information provided by the underlying database. In this tutorial, we present an excursus over the main example-based methods for exploratory analysis. We show how different data types require different techniques, and present algorithms that are specifically designed for relational, textual, and graph data. We conclude by providing a unifying view of this query-paradigm and identify new exciting research directions.

Original languageEnglish
Title of host publicationSIGIR 2019 - Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval
Number of pages2
PublisherAssociation for Computing Machinery
Publication year2019
Pages1411-1412
ISBN (Electronic)9781450361729
DOIs
Publication statusPublished - 2019
Event42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019 - Paris, France
Duration: 21 Jul 201925 Jul 2019

Conference

Conference42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019
LandFrance
ByParis
Periode21/07/201925/07/2019
SponsorACM SIGIR

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