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A bag-of-entities approach to document focus time estimation

Contributo in Atti di convegno
Data di Pubblicazione:
2017
Abstract:
Detecting the document focus time, defined as the time the content of a document refers to, is an important task to support temporal information retrieval systems. In this paper we propose a novel approach to focus time estimation based on a bag-of-entity representation. In particular, we are interested in understanding if and to what extent existing open data sources can be leveraged to achieve focus time estimation. We leverage state of the art Named Entity Extraction tools and exploit links to Wikipedia and DBpedia to derive temporal information relevant to entities, namely years and intervals of years. We then estimate focus time as the point in time that is more relevant to the entity set associated to a document. Our method does not rely on explicit temporal expressions in the documents, so it is therefore applicable to a general context. We tested our methodology on two datasets of historical events and evaluated it against a state of the art approach, measuring improvement in average estimation error.
Tipologia CRIS:
4.1 Contributo in Atti di convegno
Keywords:
Bag-of-entities; Dbpedia; Focus time; Information retrieval; Linked data; Temporal mining; Wikipedia; Computer Science
Elenco autori:
Morbidoni, Christian; Cucchiarelli, Alessandro
Autori di Ateneo:
MORBIDONI Christian
Link alla scheda completa:
https://ricerca.unich.it/handle/11564/740627
Link al Full Text:
https://ricerca.unich.it//retrieve/handle/11564/740627/396343/paper-06.pdf
Titolo del libro:
KDWEB 2017: Knowledge Discovery on the Web
Pubblicato in:
CEUR WORKSHOP PROCEEDINGS
Journal
CEUR WORKSHOP PROCEEDINGS
Series
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URL

http://ceur-ws.org/Vol-1959/paper-06.pdf
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