de.mpg.escidoc.pubman.appbase.FacesBean
Deutsch
 
Hilfe Wegweiser Impressum Kontakt Einloggen
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Bericht

Diversifying Search Results Using Time

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons101674

Gupta,  Dhruv
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44119

Berberich,  Klaus
Databases and Information Systems, MPI for Informatics, Max Planck Society;

Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)

MPI-I-2016-5-001.pdf
(beliebiger Volltext), 444KB

Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Gupta, D., & Berberich, K.(2016). Diversifying Search Results Using Time (MPI-I-2016-5-001). Saarbrücken: Max-Planck-Institut für Informatik.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-002A-0AA4-C
Zusammenfassung
Getting an overview of a historic entity or event can be difficult in search results, especially if important dates concerning the entity or event are not known beforehand. For such information needs, users would benefit if returned results covered diverse dates, thus giving an overview of what has happened throughout history. Diversifying search results based on important dates can be a building block for applications, for instance, in digital humanities. Historians would thus be able to quickly explore longitudinal document collections by querying for entities or events without knowing associated important dates apriori. In this work, we describe an approach to diversify search results using temporal expressions (e.g., in the 1990s) from their contents. Our approach first identifies time intervals of interest to the given keyword query based on pseudo-relevant documents. It then re-ranks query results so as to maximize the coverage of identified time intervals. We present a novel and objective evaluation for our proposed approach. We test the effectiveness of our methods on the New York Times Annotated corpus and the Living Knowledge corpus, collectively consisting of around 6 million documents. Using history-oriented queries and encyclopedic resources we show that our method indeed is able to present search results diversified along time.