Text segmentation using named entity recognition and co-reference
resolution in greek texts

dc.contributor.author	Φράγκου, Παυλίνα	el
dc.contributor.author	Fragkou, Pavlina	en
dc.date.accessioned	2015-04-25T09:08:52Z
dc.date.available	2015-04-25T09:08:52Z
dc.date.issued	2015-04-25
dc.identifier.uri	http://hdl.handle.net/11400/8909
dc.rights	Default License
dc.source	http://history.icininfo.net/2011/	el
dc.source	http://history.icininfo.net/2011/FileStore/procs_INFO_2011.pdf	el
dc.subject	Text segmentation
dc.subject	Κατάτμηση κειμένου
dc.subject	Named entity recognition
dc.subject	Αναγνώριση οντότητας
dc.subject	Co-reference resolution
dc.subject	Συν-αναφορά ψήφισμα
dc.subject	Information extraction
dc.subject	Εξαγωγή πληροφορίας
dc.title	Text segmentation using named entity recognition and co-reference resolution in greek texts	en
heal.type	conferenceItem
heal.classification	Information sciences
heal.classification	Library science
heal.classification	Πληροφόρηση, Επιστήμη της Πληροφόρησης
heal.classification	Βιβλιοθηκονομία
heal.classificationURI	http://skos.um.es/unescothes/C01988
heal.classificationURI	http://skos.um.es/unescothes/C02286
heal.classificationURI	N/A-Πληροφόρηση, Επιστήμη της Πληροφόρησης
heal.classificationURI	N/A-Βιβλιοθηκονομία
heal.contributorName	Γιαννακόπουλος, Γεώργιος Α. (συντ.)	el
heal.contributorName	Σακκάς, Δαμιανός Π. (συντ.)	el
heal.language	en
heal.access	free
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας. Σχολή Διοίκησης και Οικονομίας. Τμήμα Βιβλιοθηκονομίας και Συστημάτων Πληροφόρησης	el
heal.publicationDate	2011-09
heal.bibliographicCitation	Fragkou, P. (2011) Text segmentation using named entity recognition and co-reference resoluion in greek texts. In "International Conference on Integrated Information (IC-ININFO 2011)" Kos Island, Greece, 29 September - 3 Octomber 2011. pp. 34-41. Available from: http://history.icininfo.net/2011/FileStore/procs_INFO_2011.pdf [Accessed: 24/04/20105]	en
heal.abstract	In this paper we examine the benefit of performing named entity recognition and co-reference resolution to a Greek corpus used for text segmentation. Segments consist of portions among one of the 300 documents published by ten different authors in the Greek newspaper "To Vima". The aim here is to examine whether the combination of text segmentation and information extraction (and most specifically the named entity recognition and co-reference resolution steps) can prove to be beneficial for the identification of the various topics that appear in a document. Named entity recognition was performed using an already existing tool which was trained on a similar corpus. The produced annotations were manually corrected and enriched in order to cover four types of named entities (i.e. person name, organization, location and time). Coreference resolution and most specifically substitution of every reference of the same instance with the same named entity identifier was performed in a subsequent step. The evaluation using three well known text segmentation algorithms leads to the conclusion that, the benefit highly depends on the segment's topic, the number of named entity instances appearing in it, as well as the segment's length.	en
heal.fullTextAvailability	true
heal.conferenceName	International Conference on Integrated Information (IC-ININFO 2011)	el
heal.conferenceItemType	full paper