Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/16964
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dc.contributor.authorDingli, Alexiei
dc.date.accessioned2017-03-04T19:32:18Z
dc.date.available2017-03-04T19:32:18Z
dc.date.issued2003
dc.identifier.citationDingli, A. (2003). Next generation annotation interfaces for adaptive information extraction. 6th Annual Computer Linguists UK Research Colloquium, Edinburgh. 1-5.en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar//handle/123456789/16964
dc.description.abstractThe evolution of the Internet into the largest existent digital library is bringing about new challenges. One of the biggest problems is the location of information. The most promising approach seems to be performing searches semantically however this cannot work without semantically annotated documents. These documents are few and the manual annotation process to make them is both time consuming and error prone. To solve this problem Information Extraction (IE) technologies can be used to automatically annotate these documents, but be- fore doing so, IE tools require training examples. These examples are normally created manually by human annotators. Currently, there exist very few tools designed to support such people. This paper proposes a methodology aimed at supporting annotators by reducing the number of annotations required by an IE system therefore having effective learning. The whole methodology is implemented in the Melita system which will also be described in this paper. Finally enhancements to the existing methodology are being proposed in order to make IE accessible to a wider range of users, from inexperienced to expert users.en_GB
dc.language.isoenen_GB
dc.publisherComputational Linguistics UKen_GB
dc.rightsinfo:eu-repo/semantics/openAccessen_GB
dc.subjectSemantic Weben_GB
dc.subjectComputational linguisticsen_GB
dc.subjectNatural language processing (Computer science)en_GB
dc.subjectInformation organizationen_GB
dc.subjectSelf-adaptive softwareen_GB
dc.titleNext generation annotation interfaces for adaptive information extractionen_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.conferencename6th Annual Computer Linguists UK Research Colloquiumen_GB
dc.bibliographicCitation.conferenceplaceEdinburgh, United Kingdom, 6-7/01/2002en_GB
dc.description.reviewedpeer-revieweden_GB
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