Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/91882
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dc.contributor.authorEllul, Charlene-
dc.contributor.authorAzzopardi, Joel-
dc.contributor.authorAbela, Charlie-
dc.date.accessioned2022-03-21T11:13:09Z-
dc.date.available2022-03-21T11:13:09Z-
dc.date.issued2018-
dc.identifier.citationEllul, C., Abela, C., & Azzopardi, J. (2018). Extracting information from medieval notarial deeds. 21st International Conference on Knowledge Engineering and Knowledge Management (EKAW), Nancy, 25-28.en_GB
dc.identifier.issn16130073-
dc.identifier.urihttp://ceur-ws.org/-
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/91882-
dc.description.abstractThe Notarial Archives in Valletta houses a collection of Latin Notarial deeds that has not been exploited yet. In this paper, Machine Learning techniques are proposed and implemented to extract entities such as people, place names, dates, deed types and keywords from these historical texts. Both supervised and unsupervised techniques are considered and compared with baseline models. Experimental results on a subset of these documents are already showing results that outperform the baselines for Latin text such as those from CLTK. Evaluation was carried out using indexes of four published Notarial Registers.en_GB
dc.language.isoenen_GB
dc.publisherCEURen_GB
dc.rightsinfo:eu-repo/semantics/openAccessen_GB
dc.subjectKnowledge representation (Information theory)en_GB
dc.subjectMachine learning -- Techniqueen_GB
dc.subjectInformation visualization -- Maltaen_GB
dc.subjectNotarial Archives (Valletta, Malta)en_GB
dc.subjectManuscripts -- Data processingen_GB
dc.titleExtracting information from medieval notarial deedsen_GB
dc.typeconferenceObjecten_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.en_GB
dc.bibliographicCitation.conferencenameInternational Conference on Knowledge Engineering and Knowledge Management (EKAW) 2018en_GB
dc.bibliographicCitation.conferenceplaceNancy, France, 12-16/11/2018en_GB
dc.description.reviewedpeer-revieweden_GB
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