Searching Web 2.0 data through entity-based aggregation

Ekaterini Ioannou, Yannis Velegrakis

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Abstract

Entity-based searching has been introduced as a way of allowing users and applications to retrieve information about a specific real world object such as a person, an event, or a location. Recent advances in crawling, information extraction, and data exchange technologies have brought a new era in data management, typically referred to through the term Web 2.0. Entity searching over Web 2.0 data facilitates the retrieval of relevant information from the plethora of data available in semantic and social web applications.

Effective entity searching over a variety of sources requires the integration of the different pieces of information that refer to the same real world entity. Entity-based aggregation of Web 2.0 data is an effective mechanism towards this direction. Adopting the suggestions of the Linked Data movement, aggregators are able to efficiently match and merge the data that refer to the same real world object.
Original languageEnglish
Title of host publicationTransactions on Computational Collective Intelligence XXI
Place of PublicationBerlin, Heidelberg
PublisherSpringer
Pages159-174
DOIs
Publication statusPublished - 2016
Externally publishedYes

Keywords

  • semantic web
  • data integration
  • semantic data management

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