Better contextual suggestions in ClueWeb12 using domain knowledge inferred from the open web
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
National Institute of Standards and Technology (NIST)Date
2014Citation
Proceedings of The Twenty-Third Text REtrieval Conference, TREC 2014, Gaithersburg, Maryland, USA, November 19-21, 2014. Ed. Ellen M. Voorhees, Angela Ellis. National Institute of Standards and Technology (NIST), 2014Funded by
This research was supported by the Netherlands Organization for Scientific Research (NWO project #640.005.001)Editor's Version
http://trec.nist.gov/pubs/trec23/trec2014.htmlSubjects
InformáticaNote
Proceedings of the 23rd Text Retrieval Conference (TREC 2014), held in Gaithersburg, Maryland, USA, on 2014Abstract
This paper provides an overview of our participation in the Contextual
Suggestion Track. The TREC 2014 Contextual Suggestion Track allowed participants
to submit personalized rankings using documents either from the OpenWeb
or from an archived, static Web collection, the ClueWeb12 dataset. In this paper,
we focus on filtering the entire ClueWeb12 collection to exploit domain knowledge
from touristic sites available in the Open Web. We show that the generated
recommendations to the provided user profiles and contexts improve significantly
using this inferred domain knowledge.
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Google Scholar:Samar, Thaer
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Bellogin Kouki, Alejandro
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Vries, Arjen P. de
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