Search computing: Multi-domain search on ranked data

Alessandro Bozzon*, Daniele Braga, Marco Brambilla, Stefano Ceri, Francesco Corcoglioniti, Piero Fraternali, Salvatore Vadacca

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

7 Citations (Scopus)

Abstract

We demonstrate the Search Computing framework for multi-domain queries upon ranked data collected from Web sources. Search Computing answers to queries like "Find a good Jazz concert close to a specified location, a good restaurant and a hotel at walking distance" and fills the gap between generic and domain-specific search engines, by proposing new methods, techniques, interfaces, and tools for building search-based applications spanning multiple data services. The main enabling technology is an execution engine supporting methods for rank-join execution upon ranked data sources, abstracted and wrapped by means of a unifying service model. The demo walks through the interface for formulating multi-domain queries and follows the steps of the query engine that builds the result, with the help of run-time monitors that clearly explain the system's behavior. Once results are extracted, the demonstration shows several approaches for visualizing results and exploring the information space.
Original languageEnglish
Title of host publicationProceedings of SIGMOD 2011 and PODS 2011
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages1267-1269
Number of pages3
ISBN (Print)9781450306614
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 ACM SIGMOD and 30th PODS 2011 Conference - Athens, Greece
Duration: 12 Jun 201116 Jun 2011

Conference

Conference2011 ACM SIGMOD and 30th PODS 2011 Conference
Country/TerritoryGreece
CityAthens
Period12/06/1116/06/11

Keywords

  • exploratory search
  • multi-domain queries
  • search computing

Fingerprint

Dive into the research topics of 'Search computing: Multi-domain search on ranked data'. Together they form a unique fingerprint.

Cite this